Hand-held medical-data capture-device having determination of a temperature by a microprocessor from a signal from a digital infrared sensor and having interoperation with electronic medical record systems to transmit the temperature and device information

ABSTRACT

In one implementation, an apparatus estimates body core temperature from an infrared measurement of an external source point using a cubic relationship between the body core temperature and the measurement of an external source point is described, estimates temperature from a digital infrared sensor and determines vital signs from a solid-state image transducer, or determines vital signs from a solid-state image transducer and estimates body core temperature from an infrared measurement of an external source point using a cubic relationship between the body core temperature and the measurement of an external source point; after which the estimated and/or determined information is transmitted to an external database.

RELATED APPLICATION

This application is a continuation of, and claims the benefit andpriority under 35 U.S.C. 120 of U.S. Original patent application Ser.No. 14/523,890 filed 25 Oct. 2014, which is hereby incorporated byreference in its entirety.

FIELD

This disclosure relates generally to transmitting a representation ofanimal body core temperature or other vital signs to an electronicmedical record system.

BACKGROUND

Hand-held medical-data capture-devices are stand-alone devices in whichdata is retrieved from the device by an operator who reads a temperatureor other vital sign from a display screen in the hand-held medical-datacapture-devices and then manually records the vital sign in anelectronic medical record system, which is a very slow and expensiveprocess.

BRIEF DESCRIPTION

In one aspect, an apparatus estimates body core temperature from aninfrared measurement of an external source point using a cubicrelationship between the body core temperature and the measurement of anexternal source point and transmits the apparatus estimate of body coretemperature to an external device.

In a further aspect, a non-touch biologic detector estimates body coretemperature from an infrared measurement of an external source point anddetermines vital signs from a solid-state image transducer and transmitsthe apparatus estimate of body core temperature and the vital sign to anexternal device.

In another aspect, a non-touch biologic detector determines vital signsfrom a solid-state image transducer and estimates body core temperaturefrom an infrared measurement of an external source point using a cubicrelationship between the body core temperature and the measurement of anexternal source point and transmits the apparatus estimate of body coretemperature and the vital sign to an external device.

Apparatus, systems, and methods of varying scope are described herein.In addition to the aspects and advantages described in this summary,further aspects and advantages will become apparent by reference to thedrawings and by reading the detailed description that follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an overview of an electronic medicalrecords (EMR) capture system, according to an implementation;

FIG. 2 is a block diagram of an overview of an EMR capture system havinga remote cloud based bridge, according to an implementation;

FIG. 3 is a block diagram of a non-touch biologic detector that includesa digital infrared sensor, according to an implementation;

FIG. 4 is a block diagram of a non-touch biologic detector that includesa digital infrared sensor and that does not include an analog-to-digitalconverter, according to an implementation;

FIG. 5 is a block diagram of a non-touch biologic detector that includesa digital infrared sensor and a color display device, according to animplementation;

FIG. 6 is a block diagram of apparatus that estimates a body coretemperature of an external source point from a no-touch electromagneticsensor, according to an implementation;

FIG. 7 is a block diagram of apparatus to estimate a body coretemperature from an external source point from an analog infraredsensor, according to an implementation;

FIG. 8 is a block diagram of apparatus to estimate a body coretemperature from an external source point from a digital infraredsensor, according to an implementation;

FIG. 9 is a block diagram of apparatus that estimates a body coretemperature of an external source point from a non-touch electromagneticsensor and that detects vital-signs from images captured by asolid-state image transducer, according to an implementation;

FIG. 10 is a block diagram of apparatus that estimates a body coretemperature of an external source point from an analog infrared sensorand that detects vital-signs from images captured by a solid-state imagetransducer, according to an implementation.

FIG. 11 is a block diagram of apparatus that estimates a body coretemperature of an external source point from a digital infrared sensorand that detects vital-signs from images captured by a solid-state imagetransducer, according to an implementation;

FIG. 12 is a block diagram of apparatus that estimates a body coretemperature of an external source point from a digital infrared sensor,that does not include an analog-to-digital converter and that detectsvital-signs from images captured by a solid-state image transducer,according to an implementation;

FIG. 13 is a flowchart of a method to determine a temperature from adigital infrared sensor, according to an implementation;

FIG. 14 is a flowchart of a method to display temperature colorindicators, according to an implementation of three colors;

FIG. 15 is a flowchart of a method to manage power in a non-touchbiologic detector or thermometer having a digital infrared sensor,according to an implementation;

FIG. 16 is a block diagram of an apparatus of variation amplification,according to an implementation.

FIG. 17 is a block diagram of an apparatus of variation amplification,according to an implementation.

FIG. 18 is a block diagram of an apparatus of variation amplification,according to an implementation.

FIG. 19 is a block diagram of an apparatus of variation amplification,according to an implementation.

FIG. 20 is a block diagram of an apparatus of variation amplification,according to an implementation;

FIG. 21 is a block diagram of an apparatus to generate and present anyone of a number of biological vital signs from amplified motion,according to an implementation;

FIG. 22 is a block diagram of an apparatus of variation amplification,according to an implementation;

FIG. 23 is a block diagram of an apparatus of variation amplification,according to an implementation;

FIG. 24 is an apparatus that performs variation amplification togenerate biological vital signs, according to an implementation;

FIG. 25 is a flowchart of a method of variation amplification, accordingto an implementation;

FIG. 26 is a flowchart of a method of variation amplification, accordingto an implementation that does not include a separate action ofdetermining a temporal variation;

FIG. 27 is a flowchart of a method of variation amplification, accordingto an implementation;

FIG. 28 is a flowchart of a method of variation amplification, accordingto an implementation;

FIG. 29 is a flowchart of a method of variation amplification from whichto generate and communicate biological vital signs, according to animplementation;

FIG. 30 is a flowchart of a method to estimate a body core temperaturefrom an external source point in reference to a cubic relationship,according to an implementation;

FIG. 31 is a flowchart of a method to estimate a body core temperaturefrom an external source point and other measurements in reference to acubic relationship, according to an implementation;

FIG. 32 is a block diagram of a hand-held device, according to animplementation;

FIG. 33 illustrates an example of a computer environment, according toan implementation;

FIG. 34 is a representation of a display that is presented on thedisplay device of apparatus in FIGS. 3-14 and 35-39, according to animplementation;

FIG. 35 is a portion of a schematic of a circuit board of a non-touchthermometer, according to an implementation;

FIG. 36 is a portion of the schematic of the non-touch thermometerhaving the digital IR sensor, according to an implementation;

FIG. 37 is a portion of the schematic of the non-touch thermometerhaving the digital IR sensor, according to an implementation;

FIG. 38 is a circuit that is a portion of the schematic of the non-touchthermometer having the digital IR sensor, according to animplementation;

FIG. 39 is a circuit that is a portion of the schematic of the non-touchthermometer having the digital IR sensor, according to animplementation;

FIG. 40 is a block diagram of a solid-state image transducer, accordingto an implementation; and

FIG. 41 is a block diagram of the communication subsystem, according toan implementation.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings that form a part hereof, and in which is shown byway of illustration specific implementations which may be practiced.These implementations are described in sufficient detail to enable thoseskilled in the art to practice the implementations, and it is to beunderstood that other implementations may be utilized and that logical,mechanical, electrical and other changes may be made without departingfrom the scope of the implementations. The following detaileddescription is, therefore, not to be taken in a limiting sense.

The detailed description is divided into ten sections. In the firstsection, an overview of two implementations is shown. In the secondsection, implementations of apparatus of digital non-touch thermometersand vital sign variation amplification detectors are described. In thethird section, implementations of apparatus of non-touchcubic-estimation thermometers are described. In the fourth section,implementations of apparatus of non-touch cubic estimation thermometersand vital sign detectors are described. In the fifth section, methods ofdigital infrared thermometers are described. In the sixth section,implementations of apparatus of vital sign variation amplificationdetectors are described. In the seventh section, implementations ofmethods of vital sign amplification are described. In the eighthsection, implementations of methods of non-touch cubic-estimation aredescribed. In the ninth section, hardware and operating environments inwhich implementations may be practiced are described. Finally, in thetenth section, a conclusion of the detailed description is provided.

FIG. 1 is a block diagram of an overview of an electronic medicalrecords (EMR) capture system 100, according to an implementation.

FIG. 1 shows high level components of the EMR capture system 100 thatincludes a network server 102. The network server 102 is also referredto as the “bridge 102”. The bridge 102 transfers patient measurementrecords (PMRs) 103 from hand-held medical-data capture-devices 104 toEMR systems in hospital and clinical environments. Each PMR 103 includespatient measurement data, such as vital sign 136 in FIGS. 1-7 and 7-10,estimated body temperature 412 in FIG. 4-10, vital sign 1416 in FIG.14-21, and heartrate 1910, respiratory rate 1916 and EKG 1928 in FIG.19. Examples of hand-held medical-data capture-devices 104 includenon-touch biologic detector in FIG. 1-3, apparatus that estimates a bodycore temperature 4-10, apparatus of variation amplification FIGS. 14-18and 20-22, mobile device 3000 and non-touch thermometer 3300.

The EMR capture system 100 includes two important aspects:

1. A server bridge 102 to control the flow of patient measurement datafrom hand-held medical-data capture-devices 104 to one or more externalEMR systems 105 and to manage local hand-held medical-datacapture-devices 104.

2. The transfer of patient measurement data in a PMR 103, anonymous, andother patient status information to a cloud based external EMR system105.

The bridge 102 controls and manages the flow of patient measurement datato a PMR database 108 and an EMR database 110 and provides managementservices to hand-held medical-data capture-devices 104.

The bridge 102 provides an interface to:

-   -   A wide range of proprietary EMR systems 105.    -   Location specific services, per hospital, for verification of        active operator, and if necessary, patient identifications.    -   A cloud based data repository (EMR database 105) of one or more        hand-held medical-data capture-devices 104, for the purpose of        storing all measurement records in an anonymous manner for        analysis. A setup, management and reporting mechanism also        provided.

The bridge 102 accepts communications from hand-held medical-datacapture-devices 104 to:

-   -   Data format conversion and transferring patient measurement        records to EMR systems 105.    -   Manage the firmware and configuration settings of the hand-held        medical-data capture-devices 104.    -   Determine current health and status of the hand-held        medical-data capture-devices 104.    -   Support device level protocol for communications, TCP/IP, of        that supports the following core features:        -   Authentication of connected device and bridge 102        -   Transfer of patient measurement records to Bridge 102 with            acknowledgement and acceptance by the bridge 102 or EMR            acceptance.        -   Support for dynamic update of configuration information and            recovery of health and status of the hand-held medical-data            capture-devices 104.        -   Support for firmware update mechanism of firmware of            hand-held medical-data capture-devices 104.

The EMR capture system 100 provides high availability, 24/7/365, with99.99% availability.

The EMR capture system 100 provides a scalable server system to meetoperational demands in hospital operational environments for one or bothof the following deployable cases:

1. A local network 111 at an operational site in which the bridge 102provides all features and functions in a defined operational network 111to manage a system of up to 10,000+ hand-held medical-datacapture-devices 104.

2. Remote or Cloud based site 105 in which the bridge 102 provides allservices to many individual hospital or clinical sites spread over awide geographical area, for 1,000,000+ hand-held medical-datacapture-devices 104.

The bridge 102 provides a central management system for the hand-heldmedical-data capture-devices 104 that provides at least the followingfunctions:

-   -   configuration management and update of the hand-held        medical-data capture-devices 104    -   device level firmware for all of the hand-held medical-data        capture-devices 104    -   management and reporting methods for the hand-held medical-data        capture-devices 104, covering but not limited to:        -   health and status of the hand-held medical-data            capture-devices 104        -   battery level, replacement warning of the hand-held            medical-data capture-devices 104        -   check/calibration nearing warning of the hand-held            medical-data capture-devices 104        -   rechecking due to rough handling or out of calibration            period of the hand-held medical-data capture-devices 104        -   History of use, number of measurements, frequency of use            etc. of the hand-held medical-data capture-devices 104        -   Display of current device configuration of the hand-held            medical-data capture-devices 104        -   Date/time of last device communications with each of the            hand-held medical-data capture-devices 104

The bridge 102 provides extendable features, via software updates, toallow for the addition of enhanced features without the need foradditional hardware component installation at the installation site. Thebridge 102 provides a device level commission mechanism and interfacefor the initial setup, configuration and test of hand-held medical-datacapture-devices 104 on the network 111. The bridge 102 supports medicalcapture devices that are not hand-held.

Coverage of the EMR capture system 100 in a hospital can include variouslocations, wards, ER rooms, offices, Dr's Offices etc. or anywhere whereautomatic management of patient vital sign information is required to besaved to a remote EMR system.

The hand-held medical-data capture-devices 104 can communicate with athird party network bridge 112 to provide access to data storageservices, EMR systems, hand-held medical-data capture-devices cloudstorage system etc.

Networking setup, configuration, performance characteristics etc. arealso determined and carried out by the third party bridge 112 or anotherthird party, for the operational environments. The hand-heldmedical-data capture-devices can support the network protocols forcommunication with the third party bridge 112 devices.

In some implementations, a push data model is supported by the EMRcapture system 100 between the hand-held medical-data capture-devices104 and the bridge 102 in which connection and data are initially pushedfrom the hand-held medical-data capture-device 104 to the bridge 102.Once a connection has been established and the hand-held medical-datacapture-devices 104 and the bridge 102, such as an authenticatedcommunication channel, then the roles may be reversed where the bridge102 will control the flow of information between the hand-heldmedical-data capture-devices 104 and the EMR system 105.

In some implementations, the hand-held medical-data capture-device 104are connected to the EMR capture system 100 via a WIFI connection to aWi-Fi access point 106. In other implementations, the hand-heldmedical-data capture-device 104 is connected to a docking station via awireless or physical wired connection, i.e. local isolated WIFI,Bluetooth, serial, USB, etc., in which case the docking station thenacts as a local pass-through connection and connects to the bridge 102via a LAN interface.

In some implementations, the portable hand-held medical-datacapture-device 104 includes a battery with limited battery power andlifetime that in some implementations needs to be conserved in order toreduce the intervals at which the battery needs to be recharged. Theseportable hand-held medical-data capture-devices 104 support variouspower saving modes and as such each device is responsible for theinitiation of a connection to the wireless network and the subsequentconnection to the bridge 102 that meets their own specific operationalrequirements. It is expected that this will provide the hand-heldmedical-data capture-devices 104 additional control over their own powermanagement usage and lifetime.

In implementations in which the hand-held medical-data capture-devices104 attempts connection to the bridge 102, the bridge 102 is allocated astatic IP address to reduce the IP discovery burden on the hand-heldmedical-data capture-devices 104 and thus connect the hand-heldmedical-data capture-device to the bridge 102 more quickly. Morespecifically, the hand-held medical-data capture-devices 104 are notrequired to support specific discovery protocols or domain name service(DNS) in order to determine the IP address of the bridge 102. It istherefore very important that the bridge 102 IP address is static anddoes not change over the operational lifetime of EMR capture system 100on the network 111.

In some implementations installation of a new hand-held medical-datacapture-device 104 on the network 111 will require configuration of thehand-held medical-data capture-device 104 for the bridge 102 of IPaddress and other essential network configuration and securityinformation. Commissioning of a hand-held medical-data capture-device104 on the network 111 in some implementations is carried out from anmanagement interface on the bridge 102. In this way a single managementtool can be used over all lifecycle phases of a hand-held medical-datacapture-devices 104 on the network 111, such as deployment, operationaland decommissioning

In some implementations the initial network configuration of thehand-held medical-data capture-device 104 does not require the hand-heldmedical-data capture-device 104 to support any automated network levelconfiguration protocols, WPS, Zeroconfi etc. Rather the bridge 102supports a dual network configuration, one for operational use on theoperational network of the hospital or clinic, or other location, and anisolated local network, with local DHCP server, for out of the boxcommissioning of a new hand-held medical-data capture-device 104 and fordiagnostic test of the hand-held medical-data capture-devices 104.Hand-held medical-data capture-devices 104 can be factory configured forknown network settings and contain a default server IP address on thecommissioning network 111. In addition the hand-held medical-datacapture-devices 104 are required to support a protocol based command toreset the hand-held medical-data capture-device 104 to network factorydefaults for test purposes

It is commonplace that the firmware revision of the hand-heldmedical-data capture-devices 104 will not be consistent in theoperational environment. Therefore the bridge 102 is backwardscompatible with all released firmware revisions from firmware andprotocol revision, data content and device settings view point of thehand-held medical-data capture-device 104. As a result, differentrevision levels of hand-held medical-data capture-devices 104 can besupported at the same time on the network 111 by the bridge 102 for alloperations.

Implementation Alternatives

Limited Operational Features and Implementation Capability

Some implementations of the EMR capture system 100 have limitedoperational features and implementation capability. A significantfunction of the EMR capture system 100 with the limited operationalfeatures and implementation capability in the bridge 102 is to acceptdata from a hand-held medical-data capture-device 104 and update the EMRcapture system 100.

The following limited feature set in some implementations be supportedby the EMR capture system 100 for the demonstrations:

-   -   Implementation to a local IT network on a server of the local IT        network, OR located on a Cloud-based PMR storage system 105,        whichever is achievable in the time frame and meets the        operational requirements for third party EMR capture systems.    -   Acceptance of patient medical records from a hand-held        medical-data capture-device 104:        -   Date and Time        -   Operator ID        -   Patient Id        -   Patient measurement        -   Device manufacturer, model number and firmware revision    -   Acceptance of limited status information from a hand-held        medical-data capture-device 104:        -   Battery Level        -   Hospital reference        -   location reference        -   Manufacturer identification, serial number and firmware            revision        -   Unique id number    -   Transfer of patient records from a hand-held medical-data        capture-device 104, multiple hand-held medical-data        capture-devices 104 up to 10, to a third party EMR capture        system and to the EMR capture system 100, respectively in that        order.    -   Limited user interface for status review of known hand-held        medical-data capture-device 104.    -   Configuration update control for detected devices providing        configuration of:        -   Hospital reference        -   Unit location reference            Extended Operational Features and Implementation Capability

The following extended features are supported in extended operationalfeatures and implementation capability:

-   -   1. A Patient Record Information and measurement display        interface for use without an EMR capture system 100.    -   2. Update of device firmware over the wireless network.        Operational Use        Local Network Based—Single Client

In some implementations, the hand-held medical-data capture-device 104is deployed to a local hospital, or other location, wireless IT networkthat supports WI-FI enabled devices. The hand-held medical-datacapture-device 104 supports all local network policy's including anylocal security policy/protocols, such as WEP, WPA, WPA2, WPA-EPA as partof the connection process for joining the network. In someimplementations, the hand-held medical-data capture-device 104 operateson both physical and virtual wireless LAN's, WAN's, and the hand-heldmedical-data capture-device 104 is configured for operation on aspecific segment of the network. Depending on the IT network structure,when the hand-held medical-data capture-device 104 is configured foroperation on a specific segment of the network, the hand-heldmedical-data capture-devices 104 network connection ability is limitedto the areas of the operational environment for which it as beconfigured. Therefore, the hand-held medical-data capture-device 104 innetwork environments that have different network configurations isconfigured to ensure that when the hand-held medical-data capture-device104 is used in various locations throughout the environment that thehand-held medical-data capture-device 104 has access in all requiredareas.

In some implementations the bridge 102 system is located on the same ITnetwork and deployed in accordance with all local IT requirements andpolicy's and that the hand-held medical-data capture-devices 104 on thisnetwork are able to determine a routable path to the bridge 102. Thehand-held medical-data capture-devices 104 and the server are notrequired to implement any network level discovery protocols andtherefore the bridge 102 is required to be allocated static IP addresson the network. In the case where a secondary bridge 102 device isdeployed to the network as a backup for the primary, or the bridge 102supports a dual networking interface capability, then the secondarybridge 102 IP address is also required to be allocated a static IPaddress. It is important that the static IP primary and secondaryaddress, if supported, remain constant to ensure proper and continuoussystem operation. When the IP address of the bridge 102 is changed thenall devices configured with the old IP address are then unable to findthe bridge 102 device on the network and the hand-held medical-datacapture-devices 104 is manually reconfigured for operation.

A benefit of this bridge 102 implementation to the local IT networkinfrastructure is the reduction in latency times for data sent betweenthe hand-held medical-data capture-devices 104 and the bridge 102.

It is important to note that this is a single organizationimplementation and as such the bridge 102 is configured to meet thesecurity and access requirements of a single organization.

FIG. 2 is a block diagram of an overview of an electronic medicalrecords (EMR) capture system 200 having a remote cloud based bridge 102,according to an implementation.

An implementation of a remote cloud-based bridge 102 for a single clientis similar to the local network case described at the end of thedescription of FIG. 1, with the exception that the bridge 102 is notphysically located at the physical site of the hand-held medical-datacapture-devices 104. The site, such as a hospital, has deployed thebridge 102 to a remote site, their specific IT center or on aCloud-based PMR storage system 105.

The physical locale of the bridge 102 is transparent to the hand-heldmedical-data capture-device 104. However in some implementations datalatency between the bridge 102 and the hand-held medical-datacapture-devices 104 on the hand-held medical-data capture-device 104 istoo large to provide a positive user experience.

Again as in the local install case, the same user access and securitypolicies are in place for the single operating organization.

Remote Based—Multiple Client Support

In some implementations for smaller organizations or for organizationsthat do not have a supporting IT infrastructure or capability that aremote bridge 102 system is deployed to support more than oneorganization. Where the remote bridge 102 system is deployed to supportmore than one organization, the bridge 102, or servers, can be hosted asa cloud based system. In this case the hand-held medical-datacapture-devices 104 are located at the operational site for thesupported different geographical location organizations and tied to thebridge 102 via standard networking methods via either private or publicinfrastructure, or a combination thereof.

Where a remote, i.e. non-local IT network, system is deployed to supportmore than one hospital or other organization EMR capture system 100includes components that isolate each of the supported organizationssecurity and user access policy's and methods along with isolating alldata transfers and supporting each organizations data privacyrequirements. In addition system performance is required to be balancedevenly across all organizations. In this case each organization canrequire their specific EMR capture system 100 be used, their EMR capturesystem 100 will have to be concurrently operational with many diverseEMR capture systems 100.

Single Measurement Update

The primary function of the hand-held medical-data capture-device 104 isto take a patient temperature, display the result to the operator and tosave the patient information and temperature to an EMR capture system100 via the bridge 102.

Normally the hand-held medical-data capture-device 104 is in a low powerstate simply waiting for an operator to activate the unit for a patientmeasurement. Once activated by the operator EMR capture system 100 willpower up and under normal operating conditions guide the operatorthrough the process of patient temperature measurement and transmissionof the patient record to the bridge 102 for saving to the EMR capturesystem 100.

Confirmation at each stage of the process to the operator is required,i.e. data is valid, to ensure a valid identified patient result isobtained and saved to the EMR, the key confirmation point is: Saving ofdata to EMR/Bridge 102

In some implementations, the confirmation at each stage in someimplementations is provided by either the bridge 102 device or the EMRcapture system 100.

When confirmation is provided by the bridge 102 it is an acknowledgmentto the hand-held medical-data capture-device 104 that the bridge 102 hasaccepted the information for transfer to the EMR capture system 100(s)in a timely manner and is now responsible for the correct management andtransfer of that data.

When confirmation is provided by the EMR capture system(s) 100, thebridge 102 is the mechanism via which the confirmation is returned tothe hand-held medical-data capture-device 104. That is the hand-heldmedical-data capture-device 104 sends the data to the bridge 102 andthen waits for the bridge 102 to send the data to the EMR and for theEMR to respond to the bridge 102 and then the bridge 102 to thehand-held medical-data capture-device 104,

In some implementations depending on the operational network and wherethe bridge 102 is physically located, i.e. local or remote, that thetype of confirmation is configurable. For a remote located bridge 102the latency time involved in the EMR level confirmation can be deem toolong for an acceptable user experience.

In the event that the hand-held medical-data capture-device 104 cannotjoin the network or the bridge 102 device cannot be communicated with orthe bridge 102 or EMR capture system 100(s) level confirmation is notreceived the hand-held medical-data capture-device 104 will maintain aninternal non-volatile storage mechanism for unsaved patient records. Itis not acceptable for the hand-held medical-data capture-device 104 tosimply not provide its primary clinical purpose in light of thesepossible operational issue. If the hand-held medical-data capture-device104 has saved records present in its internal memory then the hand-heldmedical-data capture-device 104 will in a timely automatic mannerattempt to transfer the saved records to the bridge 102 for processing.

Heartbeat

The hand-held medical-data capture-devices 104 in order to obtaindate/time, configuration setting, provide status information to thebridge 102, transfer saved patient records and check for a firmwareupdate will provide a mechanism to on a configured intervalautomatically power up and communicate to the configured bridge 102without operator intervention.

Accordingly the and outside of the normal clinical use activation forthe hand-held medical-data capture-device 104, the hand-heldmedical-data capture-device 104 can both update its internal settings,and provide status information to the bridge 102 system.

If these actions where left to only the operator startup case of thehand-held medical-data capture-device 104 for operational clinical usethen there is an unacceptable delay to the operator in proceeding to themeasurement action of the hand-held medical-data capture-device 104.This is deemed acceptable and the hand-held medical-data capture-device104 in some implementations make best efforts to maintain itsoperational status independent of the clinical use case.

Automatic Transfer of Saved Patient Measurement Records (PMRs)

If the hand-held medical-data capture-device 104 for an unknown reasonhas been unable to either join the network or connect to the bridge 102or receive a bridge 102 or EMR capture system 100(s) level acknowledgethat data has been saved the hand-held medical-data capture-device 104will still allow the primary clinical temperature measurement functionto be carried out and will save the resultant PMR in non-volatileinternal memory up to a supported, configured, maximum number of savedpatient records on the hand-held medical-data capture-device 104.

When the hand-held medical-data capture-device 104 is started for ameasurement action the hand-held medical-data capture-device 104 willdetermine if it contains any saved patient records in its internalmemory. If one or more saved patient records are detected then thehand-held medical-data capture-device 104 will attempt to join thenetwork immediately, connect to the bridge 102 and send the patientrecords one at a time to the bridge 102 device while waiting for therequired confirmation that the bridge 102 has accepted the patientrecord. Note in this case confirmation from the EMR capture system 100is not required. On receipt of the required validation response from theremote system the hand-held medical-data capture-device 104 will deletethe patient record from its internal memory. Any saved patient recordthat is not confirmed as being accepted by the remote device ismaintained in the hand-held medical-data capture-devices 104 internalmemory for a transfer attempt on the next power up of the hand-heldmedical-data capture-device 104

The hand-held medical-data capture-device 104 on the heart beat intervalall also carry out this function. In some implementations the hand-heldmedical-data capture-device 104 will reduce its heart beat interval whensaved patient records are present on the hand-held medical-datacapture-device 104 in order to ensure that the records are transferredto the bridge 102, EMR, in a timely manner once the issue has beenresolved. When this transfer mechanism is active status information ispresented to the operator on the hand-held medical-data capture-device104 screen.

Under this operation it is possible for the bridge 102 device to receivefrom a single hand-held medical-data capture-device 104 multiple patientrecord transfer requests in rapid sequence.

Device Configuration

The hand-held medical-data capture-device 104 on connection to thebridge 102, heart beat interval or operator activated, will provide thebridge 102 with its model number and all appropriate revisions numbersand unique identification to allow the bridge 102 to determine thehand-held medical-data capture-device 104 capabilities and specificconfigurations for that device.

The hand-held medical-data capture-device 104 will query the bridge 102for its device parameters and if different from the hand-heldmedical-data capture-devices 104 current setting update the hand-heldmedical-data capture-devices 104 setting to the new setting value asprovided by the bridge 102.

Accordingly, in some implementations the bridge 102 will act as thecentral repository for device configuration, either for a single device,a group of defined devices or an entire model range.

Device Date/Time Update

In implementations where there is no mechanism on the hand-heldmedical-data capture-device(s) 104 for the user to configure date andtime on the hand-held medical-data capture-device 104 via its userinterface.

All embedded systems with a real time clock function, RTC, will driftwith time due to the accuracy of their specific RTC hardware, ambientand operational temperature.

It is therefore expected that each device on connection to the bridge102 will query the bridge 102 for the current date and time and updatethe hand-held medical-data capture-devices 104 internal RTC clock basedon the provided information.

The hand-held medical-data capture-devices 104 will query the bridge 102on the defined heart beat interval or when they are started by theoperator upon joining the network.

The bridge 102 is therefore expected to support an accurate date andtime mechanism, with leap year capability, as per the local IT policy.If no local IT policy is in place then the bridge 102 is to maintaindate and time against a known accurate source, e.g. a web based timeserver.

Accordingly, in some implementations all devices is maintained at thesame date and time across the operation of EMR capture system 100 andthe capabilities of the hand-held medical-data capture-devices 104.

Device Status Management

In some implementations the bridge 102 provides a level of devicemanagement for the hand-held medical-data capture-devices 104 being usedwith EMR capture system 100. In some implementations, the bridge 102 isable to report and determine at least the following:

-   -   Group and sort devices by manufacture, device model, revisions        information and display devices serial numbers, unique device        ID, asset number, revisions, etc. and any other localized        identification information configured into the hand-held        medical-data capture-device 104, e.g. ward location reference or        Hospital reference    -   The last time a specific unit connected to EMR capture system        100    -   The current status of the a given device, battery level, last        error, last date of re-calibration of check, or any other health        indicator supported by the hand-held medical-data capture-device        104.    -   Report devices out of their calibration period, or approaching        their calibration check    -   Report devices that require their internal battery replaced    -   Report devices that require re-checking due to a detected device        failure or error condition, or that have been treat in a harsh        manner or dropped.    -   Determine if a hand-held medical-data capture-device 104 has not        connected for a period of time and identify the hand-held        medical-data capture-device 104 as lost or stolen. If the        hand-held medical-data capture-device 104 reconnects to the        network after this period of time then the hand-held        medical-data capture-device 104 in some implementations is        highlighted as requiring an accuracy check to ensure that it is        operational. Note the hand-held medical-data capture-devices 104        will likely also support this capability and after a        pre-determined time disconnected from the network inhibit their        measurement function until a hand-held medical-data        capture-device 104 level recheck is carried out    -   Provide a mechanism to commission and decommission devices onto        and off of the network. If a hand-held medical-data        capture-device 104 has not been specifically commissioned for        operation on the network then it in some implementations is not        be allowed to access the core services supported by the bridge        102 even if it has configured for operation on the EMR capture        system 100        Firmware Update

In some implementations a firmware update for a given device model isscheduled on the network as opposed to simply occurring. It isconsidered unacceptable if a hand-held medical-data capture-device 104is activated for a patient measurement and then carries out a firmwareupdate, this delays the patient vital sign measurement.

Instead the bridge 102 system will support a firmware update roll outmechanism where the date and time of the update can be scheduled and thenumber of devices being updated concurrently can be controlled.

In some implementations, when a hand-held medical-data capture-device104 connects to the bridge 102 due to a heartbeat event that thehand-held medical-data capture-device 104 will query the bridge 102 todetermine if the firmware update for that model of device is availableand verify if its firmware, via revision number, is required to beupdated. The bridge 102 will respond to the hand-held medical-datacapture-device 104 based on if a firmware update is available and thedefined schedule for the update process.

If there is an update available but the current time and date is notvalid for the schedule then the bridge 102 will information thehand-held medical-data capture-device 104 that there is an update butthat the update process is delayed and update the hand-held medical-datacapture-devices 104 firmware check interval configuration. The firmwarecheck interval setting will then be used by the hand-held medical-datacapture-device 104 to reconnect to the bridge 102 on a faster intervalthan the heartbeat interval in order to facilitate a more rapid update.For e.g. the firmware update schedule on the bridge 102 in someimplementations is for every night between 2 pm and 4 pm, the intervaltimer in some implementations will then be set to for example, every 15minutes as opposed to a heartbeat time interval of, for example, every24 hours.

The hand-held medical-data capture-device 104 if the firmware checkinterval is non-zero will then on the firmware check interval connect tothe bridge 102 and retest for the firmware update to be carried out.Once the hand-held medical-data capture-device 104 has connected to thebridge 102 for the updated and the schedule date and time are valid,along with the concurrent number of devices being updated, the hand-heldmedical-data capture-devices 104 firmware update procedure is followed,the hand-held medical-data capture-devices 104 firmware updated and EMRcapture system 100 verified for normal operational use. As part of thefirmware update procedure the hand-held medical-data capture-devices 104firmware check internal is reset back to 0 or done so by the hand-heldmedical-data capture-device 104 on the next active condition to thebridge 102.

In some implementations the bridge 102 will manage the firmware updateprocess for many different hand-held medical-data capture-devices 104each with their specific update procedure, update file formats, andverification methods and from a date and time scheduling mechanism andthe number of devices being update concurrently. In addition in someimplementations the bridge 102 will provide a mechanism to manage andvalidate the firmware update files maintain on the bridge 102 for usewith the hand-held medical-data capture-devices 104.

This section concludes with short notes below on a number of differentaspect of the EMR data capture system 100 and 200 follow on numeroustopics:

Remote—single client: The bridge 102 architecture and implementation insome implementations cater for remote operation on a hospital networksystem. Remote operation is seen as external to the networkinfrastructure that the hand-held medical-data capture-devices 104 areoperational on but considered to be still on the organizations networkarchitecture. This can be the case where a multiple hospital—singleorganization group has deployed EMR capture system 100 but one bridge102 device services all hospital locations and the bridge 102 is locatedat one of the hospital sites or their IT center.

Remote—multiple client support: The bridge 102 architecture andimplementation in some implementations is limited to remote operation ona cloud based server that supports full functionality for more than oneindividual separate client concurrently. Where we deploy a cloud basedsingle or multiple server system to service 1 or more individualhospital/clinical organization. The IT system and security requirementsfor each client in some implementations be meet in this case, differentorganizations will have different interface requirements.

Multiple concurrent EMR support: For a single remote bridge 102servicing multiple clients EMR capture system 100 supports interfacingto an independent EMR, and different EMR vendor, concurrently for eachsupport client. With one bridge 102 servicing multiple clients eachclient can/will require the patient measurements to be sent to adifferent EMR capture system 100. These EMR capture system(s) 100 willin all likelihood be provided by different vendors.

Single organization device support: The bridge 102 supports at least10000+ hand-held medical-data capture-devices 104 for a single clientfor either local or remote implementation. Note the supported hand-heldmedical-data capture-devices 104 may be from diverse hand-heldmedical-data capture-device 104 manufacturers.

Support Different EMR for same client: The bridge 102 architecture foroperation in a single client organization supports the user by theorganization of different EMR capture system(s) 100 from differentdepartments of wards in the operational environment. It is not uncommonfor a single organization to support multiple different EMR capturesystem(s) 100 for different operational environments, for example,Cardiology and ER. EMR capture system 100 in some implementations takesthis into account and routes the patient data to the correct EMR capturesystem 100. Therefore the bridge 102 is informed for a given hand-heldmedical-data capture-device 104 which indicates to the EMR the medicaldata has to be routed to.

Segregation of operations for multiple client operations on singlebridge 102:

EMR capture system 100 supports per client interfaces and functionalityto ensure that each client's configurations, performance, user accounts,security, privacy and data protection are maintained. For single serverimplementations that service multiple independent hospital groups thebridge 102 in some implementations maintain all functionality, andperformance per client separately and ensure that separate useraccounts, bridge 102 configuration, device operation, patient andnon-patient data, ERM interfaces etc. are handled and isolated perclient. A multiple cloud based implementation in this case will obviatethis function as each client includes their own cloud based system, butthis is at a higher cost.

Multiple organization device support: The bridge 102 supports at least 1million+ hand-held medical-data capture-devices 104 for a remoteimplementations that services multiple separate hospital systems. Thesupported hand-held medical-data capture-devices 104 can be fromdifferent hand-held medical-data capture-device 104 manufacturers.

EMR capture system support: The hand-held medical-data capture-device104 supports a wide range of EMR capture system(s) 100 and is capable ofinterfacing to any commercially deployed EMR capture system 100.

EMR capture system interface and approvals: The bridge 102 deviceprovides support for all required communication, encryption, securityprotocols and data formats to support the transfer of PMR information inaccordance with all required operational, standards and approval bodiesfor EMR capture system(s) 100 supported by the EMR capture system 100.

Remote EMR capture system(s): The bridge 102 supports interfacing to therequired EMRs systems independent of the EMR capture system(s) 100location, either locally on the same network infrastructure or externalto the network that the bridge 102 is resided on or a combination ofboth. The EMR capture system 100, or systems, that the bridge 102 isrequired to interact with and save the patient to can not be located onthe same network or bridge 102 implementation location, therefore thebridge 102 implementation in some implementations ensure that the routeto the EMR exists, and is reliable.

Bridge buffering of device patient records: The bridge 102 deviceprovides a mechanism to buffer received PMRs from connected hand-heldmedical-data capture-devices 104 in the event of a communicationsfailure to the EMR capture system 100, and when communications has beenreestablished subsequently transfer the buffered measurement records tothe EMR. It is expected from time to time in normal operation that thenetwork connection from the bridge 102 to the configured EMR capturesystem 100 is lost. If communications has been lost to the configuredEMR capture system(s) 100 then the bridge 102 in some implementationsaccepts measurement records from the hand-held medical-datacapture-devices 104 and buffers the measurement records untilcommunications has be reestablished. Buffering the measurement recordsallows the medical facility to transfer the current data of the medicalfacility to the bridge 102 for secure subsequent processing. In thisevent the bridge 102 will respond to the hand-held medical-datacapture-device 104 that either 1. Dynamic validation of EMR acceptanceis not possible, or 2. The bridge 102 has accepted the data correctly.

Bridge 102 real time acknowledge of EMR save to device: The bridge 102provides a mechanism to pass to the hand-held medical-datacapture-device 104 confirmation that the EMR has accepted and saved thePMR. The bridge 102 when configured to provide the hand-heldmedical-data capture-device 104 with real time confirmation that the EMRcapture system 100(s) have accepted and validated the PMR. This is aconfiguration option supported by the bridge 102.

Bridge 102 real time acknowledgement of acceptance of device PMR: Thebridge 102 provides a mechanism to pass to the hand-held medical-datacapture-device 104 confirmation that the bridge 102 has accepted the PMRfor subsequent processing to the EMR. The hand-held medical-datacapture-device 104 in some implementations verifies that the bridge 102has accepted the PMR and informs the operator of the hand-heldmedical-data capture-device 104 that the data is secure. This level ofconfirmation to the hand-held medical-data capture-device 104 isconsidered the minimum level acceptable for use by the EMR capturesystem 100. Real time acknowledgement by the bridge 102 of acceptance ofthe PMR from the device is a configuration option supported by thebridge 102.

Bridge Date and Time: The bridge 102 maintains internal date and timeagainst the local network time source or a source recommended by the ITstaff for the network. All transitions and logging events in someimplementations are time stamped in the logs of the bridge 102. Thehand-held medical-data capture-device 104 will query the bridge 102 forthe current date and time to update its internal RTC. The internal timeof hand-held medical-data capture-device 104 can be maintained to a +/−1second accuracy level, although there is no requirement to maintain timeon the hand-held medical-data capture-device 104 to sub one-secondintervals.

Graphical User Interface: The bridge 102 device provides a graphicaluser interface to present system information to the operator, oroperators of EMR capture system 100. The user interface presented to theuser for interaction with EMR capture system 100 in some implementationsbe graphical in nature and use modern user interface practices, controlsand methods that are common use on other systems of this type. Commandline or shell interfaces are not acceptable for operator use though canbe provided for use by system admin staff.

Logging and log management: The bridge 102 is required to provide alogging capability that logs all actions carried out on the bridge 102and provides a user interface to manage the logging information.Standard logging facilities are acceptable for this function for allserver and user actions. Advanced logging of all device communicationsand data transfers in some implementations is also provided, that can beenabled/disable per hand-held medical-data capture-device or for productrange of hand-held medical-data capture-devices.

User Accounts: The bridge 102 device provides a mechanism to supportuser accounts on the hand-held medical-data capture-device 104 foraccess control purposes. Standard methods for user access control areacceptable that complies with the operational requirements for theinstall/implementation site.

User Access Control: The bridge 102 device supports multiple user accesscontrol that defines the access control privileges for each type ofuser. Multiple accounts of each supported account type are to besupport. Access to EMR capture system 100 in some implementations becontrolled at a functional level, In some implementations, the followinglevels of access is provided:

-   -   a. System Admin: provides access to all features and functions        of EMR capture system 100, server and device based.    -   Device Admin: provides access only to all device related        features and functions supported by the EMR capture system 100.    -   Device Operator: provides access only to device commissioning,        and configuration. Device Installer: provides access only to        device commissioning and test capabilities.    -   b. A user account can be configured for permissions for one or        more account types.

Multi-User Support: The bridge 102 device is required to provideconcurrent multi-user support for access and management of the bridge102 system across all functions Providing multiple user access is deemeda necessary operational feature to support.

Modify User Accounts: The bridge 102 provides a method to create,delete, and edit the supported user accounts and supported accessprivileges per account.

Bridge Data Corruption/Recovery: The bridge 102 architecture andimplementation in some implementations ensure that under an catastrophicfailure of EMR capture system 100 or a storage component that no data islost that has not been confirmed as saved to the either the EMR for PMRsor localize storage for operational data pertaining to the non-patientdata maintained by the EMR capture system 100. The bridge 102 supports amethod to ensure zero data lost under critical and catastrophic systemfailure of the bridge 102 or any of the bridge 102 components, networkinterfaces, storage systems, memory contents, etc. for any data handledby the EMR capture system 100. In the event of a recovery action where acatastrophic failure has occurred EMR capture system 100 supports boththe recovery action and its normal operational activities to ensure thatEMR capture system 100 is active for clinical use.

Bridge availability: The bridge 102 device is a high availability systemfor fail safe operation 24/7/365, with 99.99% availability, i.e. “fournines” system. The bridge 102 implementation is expected to meet anavailability metric of 99.99%, i.e. a “four nines” system because thebridge 102 hardware in some implementations is implemented with aredundant dual server configuration to handle single fault conditions.The bridge 102 is required to have an independent power source or if theinstallation site has a policy for power loss operation the bridge 102installation in some implementations comply with the policyrequirements.

Bridge 102 Static IP address and port Number: The bridge 102 provides amechanism to configure the bridge 102 for a primary use static IPaddress and port number For hand-held medical-data capture-device 104connection to the bridge 102, the bridge 102 in some implementationshave a static IP address and that IP address in some implementations beknown by the hand-held medical-data capture-device 104. Bridge 102 Dualnetwork capability: The bridge 102 system provides a mechanism tosupport a dual operational network interface to allow for failure of theprimary network interface. This secondary network interface is requiredto support a configurable static IP address and port number A redundantnetwork connection in some implementations be provided to cover theevent that the primary network interface has failed. Note if the bridge102 implementation for EMR capture system 100 employs two separatebridges 102 or other redundant mechanism to provide a backup system thenthis requirement can be relaxed from an operational view point, howeverEMR capture system 100 in some implementations support this mechanism.

Local WIFI commissioning network: The bridge 102 provides a mechanism onthe local operational network to commission new hand-held medical-datacapture-devices 104 for operational use. EMR capture system 100 is tosupply a localized isolated network for the use of commissioning newdevices onto the operational network. The bridge 102 is to have a knowndefault IP address on this network and provide a DHCP server for theallocation of IP address to devices on EMR capture system 100. Thecommissioning of new devices is to be considered a core aspect of thebridge 102 functions. However it is acceptable that a separate nonserver based application in some implementations will manage theconfiguration process provided the same user interface is presented tothe user and the same device level configuration options are provided.In some implementations, the configuration of a new hand-heldmedical-data capture-device 104 on the network is carried out in twostages: 1. Stage 1: network configuration from the commissioning networkto the operational network 2. Stage 2: Once joined on the operationalnetwork specific configuration of the hand-held medical-datacapture-device 104 for clinical/system function operation.

Remote commissioning of devices: EMR capture system 100 provides amechanism where the bridge 102 device is not present on the localnetwork for a new device is to be commissioned on the operationalnetwork. Even when the bridge 102 is on a cloud server external to theoperational site network new devices in some implementations becommissioned onto the network in the same manner as if the bridge 102was a local server. This does not preclude the installation of acommission relay server on to the operational network that supports thismechanism.

Device setup: The bridge 102 supports the configuration of a devicelevel network operation and security settings for an existing or newhand-held medical-data capture-device 104 on either the commissioningnetwork or the operational network. New devices are configured on thecommissioning network. Existing devices on the operation network arealso to be configurable for network and security requirementsIndependent of the network that the hand-held medical-datacapture-device 104 is currently connected to the bridge 102 provides therequired user interface for the configuration of the network operationaland security settings by the operator. Once configured, a method ofverifying that the hand-held medical-data capture-device 104 has beenconfigured correctly but be presented to the operator to prove that thehand-held medical-data capture-device 104 is operational. Devices areexpected support a network command to reboot and rejoin the network forthis verification purpose.

Bridge Configuration: The bridge provides a mechanism to supportconfiguration of all required bridge 102 specific control options. Amethod to configure the bridge 102 functions in some implementations isprovided for all features where a configuration option enable, disableor a range of parameters are required.

Bridge Hand-held medical-data capture-device acknowledgement method: Thebridge 102 provides a configuration method to control the type of ACKrequired to be supported by the EMR capture system 100, one of: Deviceconfiguration dependent, EMR level ack Bridge 102 level ack. In someimplementations, A hand-held medical-data capture-device 104 requiresfrom the bridge 102 an acknowledgement that the PMR has been saved bythe EMR capture system 100 or accepted for processing by the bridge 102.

EMR Level: Bridge 102 confirms save by EMR capture system 100.

Bridge Level: bridge 102 controlled, accepted for processing by thebridge 102.

Enabled/Disable of firmware updated mechanism: The bridge 102 provides amethod to globally enable or disable the supported hand-heldmedical-data capture-device 104 firmware updated feature. A globalenable/disable allows the control of the firmware update process.

Server Management: The bridge 102 is required to provide a userinterface that provides configuration and performance monitoring of thebridge 102 and platform functions.

System Reporting: The bridge 102 is required to provide a mechanism toprovide standard reports to the operator on all capabilities of thebridge 102 system. Standard reporting in some implementations includeSelection of report parameter Sorting of report parameters Printing ofreports Export of reports to known formats, WORD, excel, PDF etcIdentification of reports, organization name, location, page numbers,name of report etc Date and time of log Generate by user Type and extentof provides full reporting for all system features and logs, examplesare: List of devices known to EMR capture system 100, with locationreference and date and time of last connection Report on the batterystatus for all known hand-held medical-data capture-devices 104 Reporton any devices that reported a error Report on devices that have expiredthere calibration dates Report on devices that are approaching theircalibration dates.

Demo Patient Interface: The bridge 102 provides a mechanism for demoonly purposed where an EMR capture system 100 is not available forinterfacing to EMR capture system 100 to allow patient records receivedfrom a given device to be viewed and the vital sign data presented. Fordemonstrations of EMR capture system 100 where there is no EMR capturesystem 100 to connect the bridge 102 system to provides a user interfacemethod to present the data sent to the bridge 102 by the connectedhand-held medical-data capture-devices 104. In some implementations thispatient data interface manages and stores multiple patients and multiplerecord readings per patient and present the information to the operatorin an understandable and consistent manner.

Interface to PMR database: The bridge 102 device provides an interfaceto the PMR database 108 system for the purpose of storing anonymouspatient records and device specific status information. Anonymous PMRsare stored for the purposes of data analysis as well as provide amechanism to monitor the operation of the hand-held medical-datacapture-devices 104.

Device PMRs: The bridge 102 in some implementations accepts proprietyformatted measurement records from hand-held medical-datacapture-devices 104 connected and configured to communicate with thebridge 102 and translate the received measurement record into a suitableformat for transfer to a EMR capture system 100 The bridge 102 is thehand-held medical-data capture-device 104 that will take the hand-heldmedical-data capture-device 104 based data and translate that data intoa format suitable to pass along to a local or remote EMR system usingthe required protocols of that EMR capture system 100.

Device non patient measurement data: The bridge 102 in someimplementations accept meta data from connected hand-held medical-datacapture-devices 104 and provide meta data to a connected device. Metadata is any other data or setting parameter associated with thehand-held medical-data capture-device 104 that in some implementationsis managed by the bridge 102, e.g. device configuration settings,firmware images, status information etc.

Device to Bridge 102 interface protocol: The bridge 102 supports ahand-held medical-data capture-device 104 to bridge 102 interfaceprotocol, BRIP, for all communications between the hand-heldmedical-data capture-devices 104 and the bridge 102 device. Each devicesupports a single interface protocol, BRIF, but it in someimplementations this can be impracticable and individual device ormanufacture level protocols can have to be supported by the bridge 102,the bridge 102 architecture is therefore required to take this intoaccount.

Network communications method: The bridge 102 is required to support aLAN based interface for processing connection requests and datatransfers from remote hand-held medical-data capture-device 104.Standard communications methods such as UDP/TCP/HTTP etc. are supported,including TCP/IP sockets, but the interface is not restricted to thistransfer mechanism, the architecture of EMR capture system 100 in someimplementations support other transfer methods such as UDP, HTTP, webservers. Where more than one hand-held medical-data capture-device 104type is supported in EMR capture system 100 the bridge 102 is requiredto support different transfer mechanism concurrently Hand-heldmedical-data capture-devices 104: The bridge 102 in some implementationsaccept connections and measurement data records from hand-heldmedical-data capture-device(s) 104.

Thermometer devices: The first hand-held medical-data capture-devices104 to be supported by the EMR capture system 100 are to hand-heldmedical-data capture-device(s) 104.

Non-conforming Hand-held medical-data capture-devices: The bridge 102 insome implementations accepts connections and measurement data recordsfrom non-hand-held medical-data capture-device(s) 104 hand-heldmedical-data capture-devices 104 using device interface protocolsspecific to a given device or manufacture of a range of device. The EMRcapture system 100 supports third party hand-held medical-datacapture-devices 104 to provide the same core features and functions asthose outlined in this document. In some implementations, a core systemsupports all hand-held medical-data capture-devices 104 connected to EMRcapture system 100, for the purposes of measurement data, temperature,ECG, blood pressure, plus other vital signs, both single and continuousmeasurement based, for transfer to the selected EMR capture system 100,along with per device configuration and status monitoring.

Single Parameter Measurement Data: The bridge 102 in someimplementations accept and processes for transfer to the configured EMRcapture system 100, single event measurement data. Single eventmeasurement data is defined as a patient vital sign single pointmeasurement such as a patient temperature, blood pressure, heart rate orother data that is considered a one-time measurement event for a singlemeasurement parameter This type of data is generated from a hand-heldmedical-data capture-device 104 that supports a single vital sign.

Multiple Parameter Measurement Data: The bridge 102 in someimplementations accept and process for transfer to the EMR multipleevent measurement data. Multiple event measurement data is defined as apatient vital sign single point measurement such as a patienttemperature, blood pressure, heart rate or other parameter that isconsidered a one-time measurement event for more than one parameter Thistype of data is generated from a multi-vital sign hand-held medical-datacapture-device 104.

Continuous Parameter Measurement Data: The bridge 102 in someimplementations accept and process for transfer to the EMR singleparameter continuous measurement data. Continuous measurement data isdefined as a stream of measurement samples representing a time domainsignal for a single vital sign parameter.

Unique Hand-held medical-data capture-device ID: The bridge 102 supportsa unique identifier per hand-held medical-data capture-device 104,across all vendors and device types, for the purposes of deviceidentification, reporting and operations Each hand-held medical-datacapture-device 104 that is supported by the EMR capture system 100provides a unique ID based on the manufacture, product type, and serialnumber or other factors such as the FDA UID. The bridge 102 is requiredto track, take account of, and report this number in all interactionswith the hand-held medical-data capture-device 104 and for logging. Thisdevice ID can also be used in the authentication process when ahand-held medical-data capture-device 104 connects to the bridge 102.

Device connection authentication: The bridge 102 provides a mechanism toauthenticate a given hand-held medical-data capture-device 104 onconnection to ensure that the hand-held medical-data capture-device 104is known and allowed to transfer information to the bridge 102. Accessto the bridge 102 functions in some implementations be controlled inorder to restrict access to currently allowed devices only. Acceptanceof a hand-held medical-data capture-device 104 making connection thebridge 102 for 2 main rationales. 1. the hand-held medical-datacapture-device 104 is known to the bridge 102, and that 2.a managementfunction to control access for a given device, i.e. allow or bar access.

Device date and time update: The bridge 102 device can provide amechanism to allow a connected hand-held medical-data capture-device 104to update its internal date and time settings against the bridge 102'scurrent date and time. The hand-held medical-data capture-devices 104are to update their internal real time clocks on connection to thebridge 102, accordingly, a time reference across all devices used withEMR capture system 100 is obtained from a central source. All embeddedsystems real time clock functions drift with time and operational andambient temperature, this mechanism will form the basis of both time anddate configuration on the hand-held medical-data capture-device 104 anddynamic update of time and date for the hand-held medical-datacapture-device 104 thereby removing the need to set time and date on agiven device. An accuracy of +/−1 second is acceptable for maintainingthe time on a hand-held medical-data capture-device 104. Bridge 102 todevice backwards compatibility: The bridge 102 device is required to bebackwards compatible with all released versions of hand-heldmedical-data capture-device 104 firmware, interface protocols, and dataformats supported by the bridge 102 device from first release of thebridge 102 system. Backwards compatibly of the bridge 102 with allreleased revisions of hand-held medical-data capture-device 104 is a insome implementations for the normal operation of EMR capture system 100.It cannot be guarantee that all devices of a given product are at thesame revision level or that different products from a single manufactureor from different manufactures will support the same interface protocolor other critical component revision.

Last connection of device: The bridge 102 is required maintain a historyof the connection dates and times for a given hand-held medical-datacapture-device 104. This is required from a reporting and loggingviewpoint. In some implementations will also be used to determine if ahand-held medical-data capture-device 104 is lost/stolen or failed.

Calibration/Checker Monitoring: The bridge 102 is required to track thevalid calibration dates for a given device and present to the operatordoes devices that are out of calibration or approaching calibration Allhand-held medical-data capture-devices 104 in some implementations bechecked for operation and accuracy on a regular bases. EMR capturesystem 100 can provide the facility to generate a report and high lightdevices that are either out of calibration and those approachingcalibration. The check carried out by the bridge 102 is on the expirydate exposed by the hand-held medical-data capture-device 104. Thebridge 102 is not required to actually check the hand-held medical-datacapture-device 104 for calibration, only report if the hand-heldmedical-data capture-device 104 is out of calibration based on thehand-held medical-data capture-devices 104 expiry date. In someimplementations the expiry date is updated at the time of the hand-heldmedical-data capture-device 104 recalibration check.

Error/Issue monitoring: The bridge 102 is required to track theissues/errors reported by a given device and present that information tothe operator in terms of a system report. Reporting of device levelerrors dynamically for a given device is diagnostics tool for systemmanagement. Providing the issue/error history for a given device willprovide core system diagnostic information for the hand-heldmedical-data capture-device 104.

Battery Life monitoring: The bridge 102 is required to track the batterylevel of a given device and report the that information to the operator.EMR capture system 100 is to highlight to the operator that a givendevice has an expired or nearly expired or failed internal battery basedon the information exposed by the hand-held medical-data capture-device104. It is the hand-held medical-data capture-devices 104 responsibilityto determine its own internal power source charge level or batterycondition. The bridge 102 can provide a mechanism to report the knownbattery condition for all devices, e.g. say all devices that have 10%battery level remaining.

Lost/Stolen/Failed monitoring: The bridge 102 is required to determinefor a given hand-held medical-data capture-device 104 if it has beenlost/stolen/or failed and disable the hand-held medical-datacapture-device 104 for system operation. Being able to determine if asystem has not connected to the bridge 102 for a period of time is afeature for failed, lost or stolen reporting to the operator. If ahand-held medical-data capture-device 104 has not connected to EMRcapture system 100 for a period of time, EMR capture system 100determines that the hand-held medical-data capture-device 104 has beenstolen or lost, in this event the operator is informed in terms of asystem report and the hand-held medical-data capture-device 104 removedfrom the supported devices list. If and when the hand-held medical-datacapture-device 104 reconnects to EMR capture system 100 the hand-heldmedical-data capture-device 104 is to be lighted as “detected” andforced to be rechecked and re-commissioned again for use on the network.

Device Keep Alive: The bridge 102 provides a mechanism to inform atarget hand-held medical-data capture-device 104 upon connection to thebridge 102 to stay connected to the bridge 102 until released by thebridge 102. A hand-held medical-data capture-device 104 keep alivemethod in some implementations is provided so that the bridge 102 when ahand-held medical-data capture-device 104 connects can inform thehand-held medical-data capture-device 104 to stay powered and connectedto the bridge 102 for the purposes of reconfiguration, status monitoringor diagnostics.

Reset device to network default: A method to reset a target device orgroup of selected devices to factory settings for all network parametersin some implementations be supported.

Reset device to factory default: A method to reset a target device orgroup of selected devices to their factory default settings in someimplementations is supported.

Dynamic Device Parameter Configuration: The bridge 102 provides amechanism to provide configuration information to a hand-heldmedical-data capture-device 104 when requested by the hand-heldmedical-data capture-device 104 on connection to the bridge 102 or viathe keep device alive mechanism. Upon connecting to a bridge 102 ahand-held medical-data capture-device 104 as part of the communicationsprotocol will determine if its current configuration is out of date, ifany aspect of the hand-held medical-data capture-devices 104configuration is out of date and is required to be updated then thebridge 102 provides the current configuration information for thehand-held medical-data capture-device 104 model and revision This isintended to be as simple as the hand-held medical-data capture-device104 getting the configuration setting for each of its supportedparameters. the bridge 102 is responsible to ensure that the suppliedinformation is correct for the hand-held medical-data capture-device 104model and revision level.

Device Configuration Grouping: Single device: The bridge 102 provides amechanism to configure a single device, based on unique device id, toknown configuration parameters. The bridge 102 in some implementationsallows a single hand-held medical-data capture-device 104 to be updatedwhen it connects to the bridge 102 either via the heart beat method orvia operator use. This effectively means that the bridge 102 provides amethod to manage and maintain individual device configuration settingsand have those settings available dynamically for when the hand-heldmedical-data capture-device 104 connects. Further the bridge 102 isrequired to support per device configurations for different revisions ofdevice firmware, for example rev 1 of device A has configure parametersx, y and z, but revision 2 of the hand-held medical-data capture-device104 has configuration parameters has x, y, z and k and the valid allowedrange for the y parameter has been reduced.

Device Configuration Grouping—Hand-held medical-data capture-device 104model group: The bridge 102 provides a mechanism to configure alldevices within a model range to known configuration parameters. Thefacility to reconfigure a selected sub-group of devices that are model xand at revision level all with the same configuration information.

Device Configuration Grouping—selected group within model range: Thebridge 102 provides a mechanism to configure a selected number ofdevices within the same model range to known configuration parameters.The facility to reconfigure a selected sub-group of devices that aremodel x and at revision level y Device Configuration Grouping—definedsub group: The bridge 102 provides a mechanism to configure a selectednumber of devices with the same model based on device characteristicse.g. revision level, operational location etc. The facility toreconfigure all devices that are model x and at revision level y, OR allmodel x devices that are in operation in Ward 6 is a feature.

Device Configuration files: The bridge 102 provides a method to save,load, update and edit a configuration file for a hand-held medical-datacapture-device 104 model number and/or group settings. The ability tosave and load configuration files and change the configuration contentin the file is a required feature for EMR capture system 100. A filemanagement mechanism in some implementations is also provided for thesaved configuration files.

Dynamic configuration content: The bridge 102 in some implementationsdynamically per hand-held medical-data capture-device 104 connectiondetermine upon request by the hand-held medical-data capture-device 104the new configuration settings for that device, Given that the medialdevices will connect in a random manner to the bridge 102, the bridge102 is required for the connected device, model, revision, unique IDetc. to maintain the configuration settings for that device.

Association of hand-held medical-data capture-device 104 to target EMRcapture system(s) 100: The bridge 102 provides a mechanism to controlthe patient record received from a hand-held medical-data capture-device104 to transfer the record to one of more of the supported EMR capturesystem(s) 100. Where more than one EMR capture system 100 is maintainedby a single organization, e.g. one for ER, cardiology use andpossibility one for outpatients etc. EMR capture system 100 in someimplementations manage either by specific device configuration or bridge102 configuration which EMR the patient record is to be transmitted toby the bridge 102.

Device Configuration and Status Display: In some implementations, when ahand-held medical-data capture-device 104 connects to the bridge 102that the hand-held medical-data capture-device 104 will query itscurrent configuration settings against the bridge 102 settings for thatspecific device type and device as outlined below: 1. A given devicebased on a unique id for that device. Note each device is required to beuniquely identified in EMR capture system 100. 2. A group of devicesallocated to a physical location in the hospital, i.e. Based on a wardnumber of other unique location reference. Accordingly, in someimplementations a group of devices in a given location in someimplementations is updated separately from other devices of the sametype located in a different location in the same hospital environment,i.e. recovery ward 1 as opposed to ER 1. 3. A group of devices based onproduct type, i.e. all MD3 hand-held medical-data capture-device(s) 104,updated with the same settings. Bridge 102 device configuration optionsadjusted based on hand-held medical-data capture-device 104. The bridge102 in some implementations adjusts the configuration options presentedto the operator based on the capabilities of the hand-held medical-datacapture-device 104 being configured. Where multiple different hand-heldmedical-data capture-devices 104 are supported by the EMR capture system100 it cannot be assumed that each device from a different manufactureor from the same manufacture but a different model will have the samedevice level configuration parameters Therefore the bridge 102 in someimplementations determine the configuration capabilities for thehand-held medical-data capture-device 104 to be configured and presentonly valid configuration options for that device with valid para rangesfor these options.

Device parameter Validation: The bridge 102 provides a mechanism for agiven model of hand-held medical-data capture-device 104 to validatethat a given configuration parameter is set within valid parameterranges for that device model and revision. The bridge 102 is requiredbased on the hand-held medical-data capture-device 104 model andrevision level to present valid parameter ranges for the operator toconfigure a hand-held medical-data capture-device 104 level parameterwith. Device patient record acceptance check response source. The bridge102 provides a mechanism to configure the hand-held medical-datacapture-device 104 to require either: 1. A confirmation from the bridge102 device only that a patient record has been received for processing2. A confirmation from the bridge 102 device that the EMR capture system100 has received and saved the patient information. In someimplementations of the configuration of the hand-held medical-datacapture-device 104 the hand-held medical-data capture-device 104 reportsto the operator a status indicator.

Device Hospital/Clinic Reference: A device setting to allow anorganization identifier to be configured on the hand-held medical-datacapture-device 104. The hand-held medical-data capture-device 104 can beconfigured with an alphanumeric identification string, max 30 charactersthat allows the organization to indicate to the Hospital/clinic that thehand-held medical-data capture-device 104 is in use with, e.g. “BostonGeneral”.

Device Ward Location reference: A device setting to allow an operationallocation identifier to be configured on the hand-held medical-datacapture-device 104. The hand-held medical-data capture-device 104 is tobe configured with an alphanumeric identification string, max 30characters that allows the organization to indicate an operational areawithin the organization, e.g. “General Ward #5”.

Device Asset Number: A device setting to allow an organization assetnumber to be configured on the hand-held medical-data capture-device 104The hand-held medical-data capture-device 104 is to be configured withan alphanumeric identification string, max 30 characters to allow theorganization to provide an asset tag for the hand-held medical-datacapture-device 104.

Display device Manufacture Name, Device Model and Serial Number: Amethod to display the manufacture name, device model number and deviceserial number for the unit is provided. EMR capture system 100 canprovide a method to determine the manufacture name, model number anddevice level serial number of for the hand-held medical-datacapture-device 104 for display purposes only Alphanumeric identificationstring, max 60 characters in length for each of the three parameters.

Display hand-held medical-data capture-device 104 unique ID referencetag: A method to display the device level unique identifier for theunit. For regulatory traceability reasons each device is to support aunique identification number this number in some implementations bedisplayed by the EMR capture system 100. In some implementations, analphanumeric identification string is a maximum of 120 characters. Thisparameter is not to be updateable by the EMR capture system 100.

Device last Check/Calibration Date: A method to display and set the dateof the last check or re-calibration action for the hand-heldmedical-data capture-device 104. This will allow the bridge 102 todetermine which devices are required to be re-checked and present thatinformation to the operator of EMR capture system 100. All hand-heldmedical-data capture-devices 104 with a measurement function arerequired to be checked for accuracy on a regular basis. EMR capturesystem 100 provides a mechanism to update the hand-held medical-datacapture-device 104 date of last check/calibration when a device levelcheck has been carried out.

Device Temperature Display units: Configuration option for the displayedtemperature units for the hand-held medical-data capture-device 104,Centigrade or Fahrenheit. For patient temperature result the unit insome implementations be configured for reporting temperatures in degreescentigrade or Fahrenheit. Default is: Fahrenheit Note this is for devicelevel reporting to the operator for the hand-held medical-datacapture-device 104, the hand-held medical-data capture-device 104 willreport all temperatures in Kelvin. The bridge 102 will also require aconfiguration parameter for the display of any temperature results.

Operator scan enable/disable: The bridge 102 can provide a mechanism toenable or disable the hand-held medical-data capture-device 104 leveloperator ID scan action. The operator ID scan capability is to beconfigurable on a per device basis so that it can be enabled ordisabled. Allow Operator Scan Repeat for more than one patient scan: Thebridge 102 can provide a mechanism to enable/disable the hand-heldmedical-data capture-device 104 to take a single operator ID scan andassociate that id with multiple patient measurements. Where the clinicalwork flow allows for a known number of patient scans, or predeterminedtime frame, to be taken by a single operator an enable/disable featurefor the hand-held medical-data capture-device 104 is to be provided.Default is: disabled Max number of patient scans per operator scan: Thebridge 102 can provide a configuration parameter for controlling thenumber of patient id scans after an operator ID scan before the operatorID scan has to be taken again by the hand-held medical-datacapture-device 104. A number 1 to 12 The number of patient scans thatare allowed to be taken by the hand-held medical-data capture-device 104and assigned the same operator ID Default: 1 Max time for multiplepatient scans to one operator scan: The bridge 102 can provide aconfiguration parameter for controlling the time frame in seconds that asingle operator ID scan can be used for multiple patient id scans. Atime limit in seconds 0 to (30*60) seconds, to allow a hand-heldmedical-data capture-device 104 to associate a single operator ID withmultiple patient records in this time. In some implementations, aparameter of 0 disables the time limit range checking. The default is 0.

Digital Non-Touch Thermometers and Vital Sign Motion AmplificationDetectors Apparatus Implementations

FIG. 3 is a block diagram of a non-touch biologic detector 300 thatincludes a digital infrared sensor, according to an implementation.Non-touch biologic detector 300 is an apparatus to measure temperatureand other vital signs.

The non-touch biologic detector 300 includes a microprocessor 302. Thenon-touch biologic detector 300 includes a battery 304, a single button306 and a digital infrared sensor 308 that is operably coupled to themicroprocessor 302. The digital infrared sensor 308 includes digitalports 310 that provide only digital readout signal 312. The non-touchbiologic detector 300 includes a display device 314 that is operablycoupled to the microprocessor 302. The microprocessor 302 is operable toreceive from the digital ports 310 that provide only digital readoutsignal 312. The digital readout signal 312 is representative of aninfrared signal 316 detected by the digital infrared sensor 308. Atemperature estimator 318 in the microprocessor 302 is operable toestimate the temperature 320 from the digital readout signal 312 that isrepresentative of the infrared signal 316, a representation of anambient air temperature reading from an ambient air sensor 322, arepresentation of a calibration difference from a memory location thatstores a calibration difference 324 and a memory location that stores arepresentation of a bias 326 in consideration of a temperature sensingmode.

Some implementations of the non-touch biologic detector 300 include asolid-state image transducer 328 that is operably coupled to themicroprocessor 302 and is operable to provide two or more images 330 toa temporal-variation-amplifier 332 and a vital sign generator 334 in themicroprocessor 302 to estimate one or more vital signs 336 that aredisplayed on the display device 314.

The non-touch biologic detector 300 also includes a wirelesscommunication subsystem 338 or other external communication subsystemsuch as an Ethernet port, that provides communication to the EMR capturesystem 100. In some implementations, the wireless communicationsubsystem 338 is communication subsystem 3204 in FIG. 41.

In some implementations, the digital IR sensor 308 is a low noiseamplifier, 17-bit ADC and powerful DSP unit through which high accuracyand resolution of the estimated body temperature 320 by the apparatus inFIGS. 3-5, 8, 11-12 and 35-39 is achieved.

In some implementations, the digital IR sensor 308, 10-bit pulse widthmodulation (PWM) is configured to continuously transmit the measuredtemperature in range of −20 . . . 120° C., with an output resolution of0.14° C. The factory default power on reset (POR) setting is SMBus.

In some implementations, the digital IR sensor 308 is packaged in anindustry standard TO-39 package.

In some implementations, the generated object and ambient temperaturesare available in RAM of the digital IR sensor 308 with resolution of0.01° C. The temperatures are accessible by 2 wire serial SMBuscompatible protocol (0.02° C. resolution) or via 10-bit PWM (Pulse WidthModulated) output of the digital IR sensor 308.

In some implementations, the digital IR sensor 308 is factory calibratedin wide temperature ranges: −40 . . . 85° C. for the ambient temperatureand −70 . . . 380° C. for the object temperature.

In some implementations of the digital IR sensor 308, the measured valueis the average temperature of all objects in the Field Of View (FOV) ofthe sensor. In some implementations, the digital IR sensor 308 has astandard accuracy of ±0.5° C. around room temperatures, and in someimplementations, the digital IR sensor 308 has an accuracy of ±0.2° C.in a limited temperature range around the human body temperature.

These accuracies are only guaranteed and achievable when the sensor isin thermal equilibrium and under isothermal conditions (there are notemperature differences across the sensor package). The accuracy of thedetector can be influenced by temperature differences in the packageinduced by causes like (among others): Hot electronics behind thesensor, heaters/coolers behind or beside the sensor or by a hot/coldobject very close to the sensor that not only heats the sensing elementin the detector but also the detector package. In some implementationsof the digital IR sensor 308, the thermal gradients are measuredinternally and the measured temperature is compensated in considerationof the thermal gradients, but the effect is not totally eliminated. Itis therefore important to avoid the causes of thermal gradients as muchas possible or to shield the sensor from the thermal gradients.

In some implementations, the digital IR sensor 308 is calibrated for anobject emissivity of 1, but in some implementations, the digital IRsensor 308 is calibrated for any emissivity in the range 0.1 . . . 1.0without the need of recalibration with a black body.

In some implementations of the digital IR sensor 308, the PWM can beeasily customized for virtually any range desired by the customer bychanging the content of 2 EEPROM cells. Changing the content of 2 EEPROMcells has no effect on the factory calibration of the device. The PWMpin can also be configured to act as a thermal relay (input is To), thusallowing for an easy and cost effective implementation in thermostats ortemperature (freezing/boiling) alert applications. The temperaturethreshold is programmable by the microprocessor 302 of the non-touchbiologic detector. In a non-touch biologic detector having a SMBussystem the programming can act as a processor interrupt that can triggerreading all slaves on the bus and to determine the precise condition.

In some implementations, the digital IR sensor 308 has an optical filter(long-wave pass) that cuts off the visible and near infra-red radiantflux is integrated in the package to provide ambient and sunlightimmunity. The wavelength pass band of the optical filter is from 5.5till 14 μm.

In some implementations, the digital IR sensor 308 is controlled by aninternal state machine, which controls the measurements and generationsof the object and ambient temperatures and does the post-processing ofthe temperatures to output the temperatures through the PWM output orthe SMBus compatible interface.

Some implementations of the non-touch biologic detector includes 2 IRsensors, the output of the IR sensors being amplified by a low noise lowoffset chopper amplifier with programmable gain, converted by a SigmaDelta modulator to a single bit stream and fed to a DSP for furtherprocessing. The signal is treated by programmable (by means of EEPROMcontend) FIR and IIR low pass filters for further reduction of thebandwidth of the input signal to achieve the desired noise performanceand refresh rate. The output of the IIR filter is the measurement resultand is available in the internal RAM. 3 different cells are available:One for the on-board temperature sensor and 2 for the IR sensors. Basedon results of the above measurements, the corresponding ambienttemperature Ta and object temperatures To are generated. Both generatedtemperatures have a resolution of 0.01° C. The data for Ta and To isread in two ways: Reading RAM cells dedicated for this purpose via the2-wire interface (0.02° C. resolution, fixed ranges), or through the PWMdigital output (10 bit resolution, configurable range). In the last stepof the measurement cycle, the measured Ta and To are resealed to thedesired output resolution of the PWM) and the regenerated data is loadedin the registers of the PWM state machine, which creates a constantfrequency with a duty cycle representing the measured data.

In some implementations, the digital IR sensor 308 includes a SCL pinfor Serial clock input for 2 wire communications protocol, whichsupports digital input only, used as the clock for SMBus compatiblecommunication. The SCL pin has the auxiliary function for building anexternal voltage regulator. When the external voltage regulator is used,the 2-wire protocol for a power supply regulator is overdriven.

In some implementations, the digital IR sensor 308 includes a slavedeviceA/PWM pin for Digital input/output. In normal mode the measuredobject temperature is accessed at this pin Pulse Width Modulated. InSMBus compatible mode the pin is automatically configured as open drainNMOS. Digital input/output, used for both the PWM output of the measuredobject temperature(s) or the digital input/output for the SMBus. In PWMmode the pin can be programmed in EEPROM to operate as Push/Pull or opendrain NMOS (open drain NMOS is factory default). In SMBus mode slavedeviceA is forced to open drain NMOS I/O, push-pull selection bitdefines PWM/Thermal relay operation. The PWM/slave deviceA pin thedigital IR sensor 308 operates as PWM output, depending on the EEPROMsettings. When WPWM is enabled, after POR the PWM/slave deviceA pin isdirectly configured as PWM output. When the digital IR sensor 308 is inPWM mode, SMBus communication is restored by a special command. In someimplementations, the digital IR sensor 308 is read via PWM or SMBuscompatible interface. Selection of PWM output is done in EEPROMconfiguration (factory default is SMBus). PWM output has twoprogrammable formats, single and dual data transmission, providingsingle wire reading of two temperatures (dual zone object or object andambient). The PWM period is derived from the on-chip oscillator and isprogrammable.

In some implementations, the digital IR sensor 308 includes a VDD pinfor External supply voltage and a VSS pin for ground.

The microprocessor 302 has read access to the RAM and EEPROM and writeaccess to 9 EEPROM cells (at addresses 0x00, 0x01, 0x02, 0x03, 0x04,0x05*, 0x0E, 0x0F, 0x09). When the access to the digital IR sensor 308is a read operation, the digital IR sensor 308 responds with 16 databits and 8 bit PEC only if its own slave address, programmed in internalEEPROM, is equal to the SA, sent by the master. A slave feature allowsconnecting up to 127 devices (SA=0x00 . . . 0x07F) with only 2 wires. Inorder to provide access to any device or to assign an address to a slavedevice before slave device is connected to the bus system, thecommunication starts with zero slave address followed by low R/W bit.When the zero slave address followed by low R/W bit sent from themicroprocessor 302, the digital IR sensor 308 responds and ignores theinternal chip code information.

In some implementations, two digital IR sensors 308 are not configuredwith the same slave address on the same bus.

In regards to bus protocol, after every received 8 bits the slave deviceshould issue ACK or NACK. When a microprocessor 302 initiatescommunication, the microprocessor 302 first sends the address of theslave and only the slave device which recognizes the address will ACK,the rest will remain silent. In case the slave device NACKs one of thebytes, the microprocessor 302 stops the communication and repeat themessage. A NACK could be received after the packet error code (PEC). ANACK after the PEC means that there is an error in the received messageand the microprocessor 302 will try resending the message. PECgeneration includes all bits except the START, REPEATED START, STOP,ACK, and NACK bits. The PEC is a CRC-8 with polynomial X8+X2+X1+1. TheMost Significant Bit of every byte is transferred first.

In single PWM output mode the settings for PWM1 data only are used. Thetemperature reading can be generated from the signal timing as:

$T_{OUT} = {\left( {\frac{2\; t_{2}}{T} \times \left( {T_{O\_ MAX} \times T_{O\_ MIN}} \right)} \right) + T_{O\_ MIN}}$

where Tmin and Tmax are the corresponding rescale coefficients in EEPROMfor the selected temperature output (Ta, object temperature range isvalid for both Tobj1 and Tobj2 as specified in the previous table) and Tis the PWM period. Tout is TO1, TO2 or Ta according to Config Register[5:4] settings.

The different time intervals t1 . . . t4 have following meaning:

t1: Start buffer. During t1 the signal is always high. t1=0.125s×T(where T is the PWM period)

t2: Valid Data Output Band, 0 . . . 1/2T. PWM output data resolution is10 bit.

t3: Error band—information for fatal error in EEPROM (double errordetected, not correctable).

t3=0.25s×T. Therefore a PWM pulse train with a duty cycle of 0.875 willindicate a fatal error in EEPROM (for single PWM format). FE means FatalError.

In regards to a format for extended PWM, the temperature transmitted inData 1 field can be generated using the following equation:

$T_{{OUT}\; 1} = {\left( {\frac{4\; t_{2}}{T} \times \left( {T_{{M{AX}}\; 1} - T_{{MIN}\; 1}} \right)} \right) + T_{{MIN}\; 1}}$

For Data 2 field the equation is:

$T_{OUT2} = {\left( {\frac{4\; t_{5}}{T} \times \left( {T_{{M{AX}}\; 2} - T_{{MIN}\; 2}} \right)} \right) + T_{{MIN}2}}$

FIG. 4 is a block diagram of a non-touch biologic detector that includesa digital infrared sensor and that does not include an analog-to-digitalconverter, according to an implementation. The non-touch biologicdetector 400 does not include an analog-to-digital (A/D) converter 402operably coupled between the digital infrared sensor 308 and themicroprocessor 302. The digital infrared sensor 308 also does notinclude analog readout ports 404. The dashed lines of the A/D converter402 and the analog readout ports 404 indicates absence of the A/Dconverter 402 and the analog readout ports 404 in the non-touch biologicdetector 400. The non-touch biologic detector 400 includes amicroprocessor 302. The non-touch biologic detector 400 includes abattery 304, a single button 306, a display device 314 and a digitalinfrared sensor 308 that is operably coupled to the microprocessor 302.No analog-to-digital converter is operably coupled between the digitalinfrared sensor 308 and the microprocessor 302. The digital infraredsensor 308 has only digital ports 310 and the digital infrared sensor308 has no analog sensor readout ports. The microprocessor 302 isoperable to receive from the digital ports 310 a digital readout signal312 that is representative of an infrared signal 316 detected by thedigital infrared sensor 308 and to determine the temperature 320 fromthe digital readout signal 312 that is representative of the infraredsignal 316.

Some implementations of the non-touch biologic detector 400 include asolid-state image transducer 328 that is operably coupled to themicroprocessor 302 and is operable to provide two or more images 330 toa temporal-variation-amplifier 332 and a vital sign generator 334 in themicroprocessor 302 to estimate one or more vital signs 336 that aredisplayed on the display device 314.

The non-touch biologic detector 400 also includes a wirelesscommunication subsystem 338 or other external communication subsystemsuch as an Ethernet port, that provides communication to the EMR capturesystem 100. In some implementations, the wireless communicationsubsystem 338 is communication subsystem 3204 in FIG. 41.

FIG. 5 is a block diagram of a non-touch biologic detector 500 thatincludes a digital infrared sensor and a color display device, accordingto an implementation. In FIG. 5, the display device 314 of FIG. 3 is aLED color display device 502.

The non-touch biologic detector 500 also includes a wirelesscommunication subsystem 338 or other external communication subsystemsuch as an Ethernet port, that provides communication to the EMR capturesystem 100. In some implementations, the wireless communicationsubsystem 338 is communication subsystem 3204 in FIG. 41.

Non-Touch Cubic-Estimation Thermometers Apparatus Implementations

FIG. 6 is a block diagram of apparatus 600 that estimates a body coretemperature of an external source point from a non-touch electromagneticsensor, according to an implementation. The apparatus 600 includes abattery 304, a single button 306, a display device 314, a non-touchelectromagnetic sensor 602 and an ambient air sensor 322 that areoperably coupled to the microprocessor 604. The microprocessor 604 isoperable to receive a representation of an infrared signal 316 of theexternal source point from the non-touch electromagnetic sensor 602. Themicroprocessor 604 includes a cubic temperature estimator 606 that isoperable to estimate the body core temperature 612 of the subject fromthe representation of the electromagnetic energy of the external sourcepoint.

The cubic temperature estimator 606 that estimates body temperature inreference to a cubic relationship that represents three thermal rangesbetween the body core temperature and the numerical representation ofthe electromagnetic energy of the external source point. The cubicrelationship includes a coefficient representative of differentrelationships between the external source point and the body coretemperature in the three thermal ranges in reference to the numericalrepresentation of the electromagnetic energy of the external sourcepoint, numerical constants for each cubic factor, ambient airtemperature and the three thermal ranges. The cubic relationship for allranges of ambient temperatures provides best results because a linear ora quadratic relationship provide inaccurate estimates of bodytemperature, yet a quartic relationship, a quintic relationship, sexticrelationship, a septic relationship or an octic relationship provideestimates along a highly irregular curve that is far too wavy ortwisting with relatively sharp deviations from one ambient temperatureto another ambient temperature.

The non-touch electromagnetic sensor 602 detects temperature in responseto remote sensing of a surface a human or animal. In someimplementations, the non-touch thermometer is an infrared temperaturesensor. All humans or animals radiate infrared energy. The intensity ofthis infrared energy depends on the temperature of the human or animal,thus the amount of infrared energy emitted by a human or animal can beinterpreted as a proxy or indication of the temperature of the human oranimal. The non-touch electromagnetic sensor 602 measures thetemperature of a human or animal based on the electromagnetic energyradiated by the human or animal. The measurement of electromagneticenergy is taken by the non-touch electromagnetic sensor 602 whichconstantly analyzes and registers the ambient temperature. When theoperator of apparatus in FIG. 3 holds the non-touch electromagneticsensor 602 about 5-8 cm (2-3 inches) from the forehead and activates theradiation sensor, the measurement is instantaneously measured. Tomeasure a temperature using the non-touch electromagnetic sensor 602,pushing the button 306 causes a reading of temperature measurement fromthe non-touch electromagnetic sensor 602 and the measured temperature isthereafter displayed on the display device 314.

Body temperature of a human or animal can be measured in many surfacelocations of the body. Most commonly, temperature measurements are takenof the forehead, mouth (oral), inner ear (tympanic), armpit (axillary)or rectum. In addition, temperature measurements are taken of a carotidartery (the external carotid artery on the right side of a human neck).An ideal place to measure temperature is the forehead in addition to thecarotid artery. When electromagnetic energy is sensed from two or moresource points, for example, the forehead and the external carotid arteryon the right side of a human neck, a cubic temperature estimator 606performs one or more of the actions in the methods that are described inFIG. 27-31. The cubic temperature estimator 606 correlates thetemperatures sensed by the non-touch electromagnetic sensor 602 from themultiple source points (e.g. the forehead and the carotid artery) toanother temperature, such as a core temperature of the subject, anaxillary temperature of the subject, a rectal temperature of the subjectand/or an oral temperature of the subject. The cubic temperatureestimator 606 can be implemented as a component on a microprocessor,such as main processor 3202 in FIG. 32, processing unit 3304 in FIG. 33or microprocessor 3504 in FIG. 35 or on a memory such as flash memory3208 in FIG. 32 or system memory 3306.

The apparatus 600 also detects the body temperature of a human or animalregardless of the room temperature because the measured temperature ofthe non-touch electromagnetic sensor 602 is adjusted in reference to theambient temperature in the air in the vicinity of the apparatus. Thehuman or animal must not have undertaken vigorous physical activityprior to temperature measurement in order to avoid a misleading hightemperature. Also, the room temperature should be moderate, 50° F. to120° F.

The apparatus 600 provides a non-invasive and non-irritating means ofmeasuring human or animal temperature to help ensure good health.

When evaluating results, the potential for daily variations intemperature can be considered. In children less than 6 months of agedaily variation is small. In children 6 months to 4 years old thevariation is about 1 degree. By age 6 variations gradually increase to 4degrees per day. In adults there is less body temperature variation.

The apparatus 600 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

FIG. 7 is a block diagram of apparatus 700 to estimate a body coretemperature from an external source point from an analog infraredsensor, according to an implementation. The apparatus 700 includes abattery 304, a single button 306, a display device 314, an analoginfrared sensor 702 and an ambient air sensor 322 that are operablycoupled to the microprocessor 604. The microprocessor 604 is operable toreceive a representation of an infrared signal 316 of the externalsource point from the analog infrared sensor 702. The microprocessor 604includes a cubic temperature estimator 606 that is operable to estimatethe body core temperature 612 of the subject from the representation ofthe electromagnetic energy of the external source point.

The apparatus 700 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

FIG. 8 is a block diagram of apparatus 800 to estimate a body coretemperature from an external source point from a digital infraredsensor, according to an implementation. The apparatus 800 includes abattery 304, a single button 306, a display device 314, a digitalinfrared sensor 308 and an ambient air sensor 322 that are operablycoupled to the microprocessor 604. The microprocessor 604 is operable toreceive a representation of an infrared signal 316 of the externalsource point from the digital infrared sensor 308. The microprocessor604 includes a cubic temperature estimator 606 that is operable toestimate the body core temperature 612 of the subject from therepresentation of the electromagnetic energy of the external sourcepoint.

The apparatus 800 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

Non-Touch Cubic-Estimation Thermometer and Vital Sign DetectionApparatus Implementations

FIG. 9 is a block diagram of apparatus 900 that estimates a body coretemperature of an external source point from a non-touch electromagneticsensor and that detects vital-signs from images captured by asolid-state image transducer, according to an implementation. Theapparatus 900 includes a battery 304, a single button 306, a displaydevice 314, a non-touch electromagnetic sensor 902 and an ambient airsensor 322 that are operably coupled to the microprocessor 902. Themicroprocessor 902 is operable to receive a representation of aninfrared signal 316 of the external source point from the non-touchelectromagnetic sensor 902. The microprocessor 902 includes a cubictemperature estimator 606 that is operable to estimate the body coretemperature 612 of the subject from the representation of theelectromagnetic energy of the external source point. The apparatus 900includes a solid-state image transducer 328 that is operably coupled tothe microprocessor 902 and is operable to provide two or more images 330to the microprocessor 902.

The apparatus 900 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

FIG. 10 is a block diagram of apparatus 1000 that estimates a body coretemperature of an external source point from an analog infrared sensorand that detects vital-signs from images captured by a solid-state imagetransducer, according to an implementation. The apparatus 1000 includesa battery 304, a single button 306, a display device 314, an analoginfrared sensor 702 and an ambient air sensor 322 that are operablycoupled to the microprocessor 902. The microprocessor 902 is operable toreceive a representation of an infrared signal 316 of the externalsource point from the analog infrared sensor 702. The microprocessor 902includes a cubic temperature estimator 606 that is operable to estimatethe body core temperature 612 of the subject from the representation ofthe electromagnetic energy of the external source point. The apparatus1000 includes a solid-state image transducer 328 that is operablycoupled to the microprocessor 902 and is operable to provide two or moreimages 330 to the microprocessor 902.

The apparatus 1000 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

FIG. 11 is a block diagram of apparatus 1100 that estimates a body coretemperature of an external source point from a digital infrared sensorand that detects vital-signs from images captured by a solid-state imagetransducer, according to an implementation. The apparatus 1100 includesa battery 304, a single button 306, a display device 314, a digitalinfrared sensor 308 and an ambient air sensor 322 that are operablycoupled to the microprocessor 902. The microprocessor 902 is operable toreceive a representation of an infrared signal 316 of the externalsource point from the digital infrared sensor 308. The microprocessor902 includes a cubic temperature estimator 606 that is operable toestimate the body core temperature 612 of the subject from therepresentation of the electromagnetic energy of the external sourcepoint. The apparatus 1100 includes a solid-state image transducer 328that is operably coupled to the microprocessor 902 and is operable toprovide two or more images 330 to the microprocessor 902.

The apparatus 1100 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

FIG. 12 is a block diagram of apparatus 1200 that estimates a body coretemperature of an external source point from a digital infrared sensor,that does not include an analog-to-digital converter and that detectsvital-signs from images captured by a solid-state image transducer,according to an implementation. The apparatus 1200 includes a battery304, a single button 306, a display device 314, a digital infraredsensor 308 and an ambient air sensor 322 that are operably coupled tothe microprocessor 902. The microprocessor 902 is operable to receive arepresentation of an infrared signal 316 of the external source pointfrom the digital infrared sensor 308. The microprocessor 902 includes acubic temperature estimator 606 that is operable to estimate the bodycore temperature 612 of the subject from the representation of theelectromagnetic energy of the external source point. The apparatus 1200includes a solid-state image transducer 328 that is operably coupled tothe microprocessor 902 and is operable to provide two or more images 330to the microprocessor 902. The apparatus 900 does not include ananalog-to-digital (A/D) converter 402 operably coupled between thedigital infrared sensor 308 and the microprocessor 902. The digitalinfrared sensor 308 also does not include analog readout ports 404. Thedashed lines of the analog-to-digital (A/D) converter 402 and the analogreadout ports 404 indicates absence of the A/D converter 402 and theanalog readout ports 404 in the apparatus 900.

The apparatus 1200 also includes a wireless communication subsystem 338or other external communication subsystem such as an Ethernet port, thatprovides communication to the EMR capture system 100. In someimplementations, the wireless communication subsystem 338 iscommunication subsystem 3204 in FIG. 41.

In regards to the structural relationship of the digital infrared sensor308 and the microprocessor 302 in FIGS. 3-5, 8 and 11-12, heat radiationon the digital infrared sensor 308 from any source such as themicroprocessor 302 or heat sink, will distort detection of infraredenergy by the digital infrared sensor 308. In order to prevent or atleast reduce heat transfer between the digital infrared sensor 308 andthe microprocessor 302, the apparatus in FIGS. 3-5, 8 and 11-12 arelow-powered devices and thus low heat-generating devices that are alsopowered by a battery 304; and that are only used for approximately a 5second period of time for each measurement (1 second to acquire thetemperature samples and generate the body core temperature result, and 4seconds to display that result to the operator) so there is little heatgenerated by the apparatus in FIGS. 3-5, 8 and 11-12 in active use.

The internal layout of the apparatus in FIGS. 3-5, 8 and 11-12 minimizesas practically as possible the digital infrared sensor as far away indistance from all other components such the microprocessor (302, 604 or902) within the practical limitations of the industrial design of theapparatus in FIGS. 3-5, 8 and 11-12.

More specifically, to prevent or at least reduce heat transfer betweenthe digital infrared sensor 308 and the microprocessor (102, 604 or 902)in some implementations the digital infrared sensor 308 is isolated on aseparate PCB from the PCB that has the microprocessor (102, 604 or 902),as shown in FIG. 34, and the two PCBs are connected by only a connectorthat has 4 pins. The minimal connection of the single connector having 4pins reduces heat transfer from the microprocessor (102, 604 or 902) tothe digital infrared sensor 308 through the electrical connector andthrough transfer that would occur through the PCB material if thedigital infrared sensor 308 and the microprocessor 302 were mounted onthe same PCB.

In some implementations, the apparatus in FIG. 3-12 includes only oneprinted circuit board, in which case the printed circuit board includesthe microprocessor 302 and the digital infrared sensor 308, non-touchelectromagnetic sensor 602 or the analog infrared sensor 702 are mountedon the singular printed circuit board. In some implementations, theapparatus in FIG. 3-12 includes two printed circuit boards, such as afirst printed circuit board and a second printed circuit board in whichthe microprocessor 302 is on the first printed circuit board and thedigital infrared sensor 308, non-touch electromagnetic sensor 602 or theanalog infrared sensor 702 are on the second printed circuit board. Insome implementations, the apparatus in FIG. 3-12 includes only onedisplay device 314, in which case the display device 314 includes notmore than one display device 314. In some implementations, the displaydevice 314 is a liquid-crystal diode (LCD) display device. In someimplementations, the display device 314 is a light-emitting diode (LED)display device. In some implementations, the apparatus in FIG. 3-12includes only one battery 304.

Digital Infrared Thermometer Method Implementations

In the previous section, apparatus of the operation of an implementationwas described. In this section, the particular methods performed byFIGS. 3-5, 8 and 11-12 are described by reference to a series offlowcharts.

FIG. 13 is a flowchart of a method 1300 to determine a temperature froma digital infrared sensor, according to an implementation. Method 1300includes receiving from the digital readout ports of a digital infraredsensor a digital signal that is representative of an infrared signaldetected by the digital infrared sensor, at block 1302. No signal thatis representative of the infrared signal is received from an analoginfrared sensor.

Method 1300 also includes determining a temperature from the digitalsignal that is representative of the infrared signal, at block 1304.

FIG. 14 is a flowchart of a method 1400 to display temperature colorindicators, according to an implementation of three colors. Method 1400provides color rendering in the color LED 3412 to indicate a generalrange of a temperature.

Method 1400 includes receiving a temperature (such as temperature 340 inFIG. 3), at block 1401.

Method 1400 also includes determining whether or not the temperature isin the range of 32.0° C. and 37.3° C., at block 1402. If the temperatureis in the range of 32.0° C. and 37.3° C., then the color is set to‘amber’ to indicate a temperature that is low, at block 1404 and thebackground of the color LED 3412 is activated in accordance with thecolor, at block 1406.

If the temperature is not the range of 32.0° C. and 37.3° C., thenmethod 1400 also includes determining whether or not the temperature isin the range of 37.4° C. and 38.0° C., at block 1408. If the sensedtemperature is in the range of 37.4° C. and 38.0° C., then the color isset to green to indicate no medical concern, at block 1410 and thebackground of the color LED 3412 is activated in accordance with thecolor, at block 1406.

If the temperature is not the range of 37.4° C. and 38.0° C., thenmethod 1400 also includes determining whether or not the temperature isover 38.0° C., at block 1412. If the temperature is over 38.0° C., thenthe color is set to ‘red’ to indicate alert, at block 1412 and thebackground of the color LED 3412 is activated in accordance with thecolor, at block 1406.

Method 1400 assumes that temperature is in gradients of 10ths of adegree. Other temperature range boundaries are used in accordance withother gradients of temperature sensing.

In some implementations, some pixels in the color LED 3412 are activatedas an amber color when the temperature is between 36.3° C. and 37.3° C.(97.3° F. to 99.1° F.), some pixels in the color LED 3412 are activatedas a green when the temperature is between 37.4° C. and 37.9° C. (99.3°F. to 100.2° F.), some pixels in the color LED 3412 are activated as ared color when the temperature is greater than 38° C. (100.4° F.). Insome implementations, the color LED 3412 is a backlit LCD screen 502 inFIG. 5 (which is easy to read in a dark room) and some pixels in thecolor LED 3412 are activated (remain lit) for about 5 seconds after thesingle button 306 is released. After the color LED 3412 has shut off,another temperature reading can be taken by the apparatus. The colorchange of the color LED 3412 is to alert the operator of the apparatusof a potential change of body temperature of the human or animalsubject. The temperature reported on the display can be used fortreatment decisions.

FIG. 15 is a flowchart of a method 1500 to manage power in a non-touchdevice having a digital infrared sensor, according to an implementation.The method 1500 manages power in the device, such as non-touch biologicdetectors and thermometers in FIG. 3-12, the non-touch thermometer 3500in FIG. 35, the hand-held device 3200 in FIG. 32 and/or the computer3300 in FIG. 33 in order to reduce heat pollution in the digitalinfrared sensor.

To prevent or at least reduce heat transfer between the digital infraredsensor 308 and the microprocessor 302, microprocessor 604,microprocessor 3504 In FIG. 35, main processor 3202 in FIG. 32 orprocessing unit 3304 in FIG. 33, the components of the non-touchbiologic detectors 300, 400 and 300 in FIG. 3-12, the non-touchthermometer 3500 in FIG. 35, the hand-held device 3200 in FIG. 32 and/orthe computer 3300 in FIG. 33 are power controlled, i.e. the non-touchbiologic detectors 300, 400 and 300 in FIG. 3-12, the non-touchthermometer 3500 in FIG. 35, the hand-held device 3200 in FIG. 32 and/orthe computer 3300 in FIG. 33 turn sub-systems on and off, and thecomponents are only activated when needed in the measurement and displayprocess, which reduces power consumption and thus heat generation by themicroprocessor 302, microprocessor 3504 In FIG. 35, main processor 3202in FIG. 32 or processing unit 3304 in FIG. 33, of the non-touch biologicdetectors 300, 400 and 300 in FIG. 3-12, the non-touch thermometer 3500in FIG. 35, the hand-held device 3200 in FIG. 32 and/or the computer3300 in FIG. 33, respectively. When not in use, at block 1502, thenon-touch biologic detectors 300, 400 and 300 in FIG. 3-12, thenon-touch thermometer 3500 in FIG. 35, the hand-held device 3200 in FIG.32 and/or the computer 3300 in FIG. 33 are completely powered-off, atblock 1504 (including the main PCB having the microprocessor 302,microprocessor 604, microprocessor 3504 In FIG. 35, main processor 3202in FIG. 32 or processing unit 3304 in FIG. 33, and the sensor PCB havingthe digital infrared sensor 308) and not drawing any power, other than apower supply, i.e. a boost regulator, which has the effect that thenon-touch biologic detectors 300, 400 and 300 in FIG. 3-12, thenon-touch thermometer 3500 in FIG. 35, the hand-held device 3200 in FIG.32 and/or the computer 3300 in FIG. 33 draw only drawing micro-amps fromthe battery 304 while in the off state, which is required for the lifetime requirement of 3 years of operation, but which also means that inthe non-use state there is very little powered circuitry in thenon-touch biologic detectors 300, 400 and 300 in FIG. 3-12, thenon-touch thermometer 3500 in FIG. 35, the hand-held device 3200 in FIG.32 and/or the computer 3300 in FIG. 33 and therefore very little heatgenerated in the non-touch biologic detectors 300, 400 and 300 in FIG.3-12, the non-touch thermometer 3500 in FIG. 35, the hand-held device3200 in FIG. 32 and/or the computer 3300 in FIG. 33.

When the non-touch biologic detectors 300, 400 and 300 in FIG. 3-12, thenon-touch thermometer 3500 in FIG. 35, the hand-held device 3200 in FIG.32 and/or the computer 3300 in FIG. 33 are started by the operator, atblock 1506, only the microprocessor 302, microprocessor 604,microprocessor 3504 In FIG. 35, main processor 3202 in FIG. 32 orprocessing unit 3304 in FIG. 33, digital infrared sensor 308, and lowpower LCD (e.g. display device 314) are turned on for the first 1second, at block 1508, to take the temperature measurement via thedigital infrared sensor 308 and generate the body core temperatureresult via the microprocessor 302 in FIG. 3-12, microprocessor 3504 inFIG. 35, main processor 3202 in FIG. 32 or processing unit 3304 in FIG.33, at block 1510. In this way, the main heat generating components (theLCD 314, the main PCB having the microprocessor 302 and the sensor PCBhaving the digital infrared sensor 308), the display back-light and thetemperature range indicator (i.e. the traffic light indicator 3412) arenot on and therefore not generating heat during the critical start-upand measurement process, no more than 1 second. After the measurementprocess of block 1510 has been completed, the digital infrared sensor308 is turned off, at block 1512, to reduce current usage from thebatteries and heat generation, and also the display back-light andtemperature range indicators are turned on, at block 1514.

The measurement result is displayed for 4 seconds, at block 1516, andthen the non-touch biologic detectors 300, 400 and 300 in FIG. 3-12, thenon-touch thermometer 3500 in FIG. 35, the hand-held device 3200 in FIG.32 and/or the computer 3300 in FIG. 33 are put in low power-off state,at block 1518.

In some implementations of methods and apparatus of FIG. 3-39 anoperator can take the temperature of a subject at multiple locations ona patient and from the temperatures at multiple locations to determinethe temperature at a number of other locations of the subject. Themultiple source points of which the electromagnetic energy is sensed aremutually exclusive to the location of the correlated temperature. In oneexample, the carotid artery source point on the subject and a foreheadsource point are mutually exclusive to the core temperature of thesubject, an axillary temperature of the subject, a rectal temperature ofthe subject and an oral temperature of the subject.

The correlation of action can include a calculation based on Formula 1:T _(body)=|ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T _(ntc)))+F4_(body)|  Formula 1

-   -   where T_(body) is the temperature of a body or subject    -   where ƒ_(stb) is a mathematical formula of a surface of a body    -   where ƒ_(ntc) is mathematical formula for ambient temperature        reading    -   where T_(surface temp) is a surface temperature determined from        the sensing.    -   where T_(ntc) is an ambient air temperature reading    -   where F4_(body) is a calibration difference in axillary mode,        which is stored or set in a memory of the apparatus either        during manufacturing or in the field. The apparatus also sets,        stores and retrieves F4_(oral), F4_(core), and F4_(rectal) in        the memory.    -   ƒ_(ntc)(T_(ntc)) is a bias in consideration of the temperature        sensing mode. For example ƒ_(axillary)(T_(axillary))=0.2° C.,        ƒ_(oral)(T_(oral))=0.4° C., ƒ_(rectal)(T_(rectal))=0.5° C. and        ƒ_(core)(T_(core))=0.3° C.

In some implementations of determining a correlated body temperature ofcarotid artery by biasing a sensed temperature of a carotid artery, thesensed temperature is biased by +0.5° C. to yield the correlated bodytemperature. In another example, the sensed temperature is biased by−0.5° C. to yield the correlated body temperature. An example ofcorrelating body temperature of a carotid artery follows:ƒ_(ntc)(T _(ntc))=0.2° C. when T _(ntc)=26.2° C. as retrieved from adata table for body sensing mode.

assumption: T_(surface temp)=37.8° C.T _(surface temp)+ƒ_(ntc)(T _(ntc))=37.8° C.+0.2° C.=38.0° C.ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T _(ntc)))=38° C.+1.4° C.=39.4° C.

assumption: F4_(body)=0.5° C.T _(body)=|ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T_(ntc)))+F4_(body)|=|39.4° C.+0.5 C|=39.9° C.

The correlated temperature for the carotid artery is 40.0° C.

In an example of correlating temperature of a plurality of externallocations, such as a forehead and a carotid artery to an axillarytemperature, first a forehead temperature is calculated using formula 1as follows:ƒ_(ntc)(T _(ntc))=0.2° C. when T _(ntc)=26.2° C. as retrieved from adata table for axillary sensing mode.

-   -   assumption: T_(surface temp)=37.8° C.        T _(surface temp)+ƒ_(ntc)(T _(ntc))=37.8° C.+0.2° C.=38.0° C.        ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T _(ntc)))=38° C.+1.4°        C.=39.4° C.    -   assumption: F4_(body)=0° C.        T _(body)=|ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T        _(ntc)))+F4_(body)|=|39.4° C.+0 C|=39.4° C.

And second, a carotid temperature is calculated using formula 1 asfollows:ƒ_(ntc)(T _(ntc))=0.6° C. when T _(ntc)=26.4° C. as retrieved from adata table.

assumption: T_(surface temp)=38.0° C.T _(surface temp)+ƒ_(ntc)(T _(ntc))=38.0° C.+0.6° C.=38.6° C.ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T _(ntc)))=38.6° C.+1.4 C=40.0° C.

assumption: F4_(body)=0° C.T _(body)=|ƒ_(stb)(T _(surface temp)+ƒ_(ntc)(T_(ntc)))+F4_(body)|=|40.0° C.+0 C|=40.0° C.

Thereafter the correlated temperature for the forehead (39.4° C.) andthe correlated temperature for the carotid artery (40.0° C.) areaveraged, yielding the final result of the scan of the forehead and thecarotid artery as 39.7° C.

Vital Sign Motion Amplification Apparatus Implementations

Apparatus in FIG. 16-24 use spatial and temporal signal processing togenerate vital signs from a series of digital images.

FIG. 16 is a block diagram of an apparatus 1600 of variationamplification, according to an implementation. Apparatus 1600 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 1600 includes a skin-pixel-identifier1602 that identifies pixel values that are representative of the skin intwo or more images 1604. In some implementations the images 1604 areframes of a video. The skin-pixel-identifier 1602 performs block 2502 inFIG. 25. Some implementations of the skin-pixel-identifier 1602 performan automatic seed point based clustering process on the two or moreimages 1604. In some implementations, apparatus 1600 includes afrequency filter 1606 that receives the output of theskin-pixel-identifier 1602 and applies a frequency filter to the outputof the skin-pixel-identifier 1602. The frequency filter 1606 performsblock 2504 in FIG. 25 to process the images 1604 in the frequencydomain. In implementations where the apparatus in FIG. 16-24 or themethods in FIG. 25-27 are implemented on non-touch biologic detectorsand thermometers in FIG. 3-10, the images 1604 in FIG. 16-24 are theimages 330 in FIG. 3-12. In some implementations the apparatus in FIG.16-22 or the methods in FIG. 25-29 are implemented on the hand-helddevice 3200 in FIG. 32.

In some implementations, apparatus 1600 includes a regional facialclusterial module 1608 that applies spatial clustering to the output ofthe frequency filter 1606. The regional facial clusterial module 1608performs block 2506 in FIG. 25. In some implementations the regionalfacial clusterial module 1608 includes fuzzy clustering, k-meansclustering, expectation-maximization process, Ward's apparatus or seedpoint based clustering.

In some implementations, apparatus 1600 includes a frequency-filter 1610that applies a frequency filter to the output of the regional facialclusterial module 1608. The frequency-filter 1610 performs block 2508 inFIG. 25. In some implementations, the frequency-filter 1610 is aone-dimensional spatial Fourier Transform, a high pass filter, a lowpass filter, a bandpass filter or a weighted bandpass filter. Someimplementations of frequency-filter 1610 includes de-noising (e.g.smoothing of the data with a Gaussian filter). The skin-pixel-identifier1602, the frequency filter 1606, the regional facial clusterial module1608 and the frequency-filter 1610 amplify temporal variations (as atemporal-variation-amplifier) in the two or more images 1604.

In some implementations, apparatus 1600 includes a temporal-variationidentifier 1612 that identifies temporal variation of the output of thefrequency-filter 1610. Thus, the temporal variation represents temporalvariation of the images 1604. The temporal-variation identifier 1612performs block 2510 in FIG. 25.

In some implementations, apparatus 1600 includes a vital-sign generator1614 that generates one or more vital sign(s) 1616 from the temporalvariation. The vital sign(s) 1616 are displayed for review by ahealthcare worker or stored in a volatile or nonvolatile memory forlater analysis, or transmitted to other devices for analysis.

Fuzzy clustering is a class of processes for cluster analysis in whichthe allocation of data points to clusters is not “hard” (all-or-nothing)but “fuzzy” in the same sense as fuzzy logic. Fuzzy logic being a formof many-valued logic which with reasoning that is approximate ratherthan fixed and exact. In fuzzy clustering, every point has a degree ofbelonging to clusters, as in fuzzy logic, rather than belongingcompletely to just one cluster. Thus, points on the edge of a cluster,may be in the cluster to a lesser degree than points in the center ofduster. An overview and comparison of different fuzzy clusteringprocesses is available. Any point x has a set of coefficients giving thedegree of being in the kth cluster w_(k)(x). With fuzzy c-means, thecentroid of a cluster is the mean of all points, weighted by a degree ofbelonging of each point to the cluster:

$c_{k} = {\frac{\sum\limits_{x}\;{{w_{k}(x)}^{m}x}}{\sum\limits_{x}\;{w_{k}(x)}^{m}}.}$

The degree of belonging, w_(k)(x), is related inversely to the distancefrom x to the cluster center as calculated on the previous pass. Thedegree of belonging, w_(k)(x) also depends on a parameter m thatcontrols how much weight is given to the closest center.

k-means clustering is a process of vector quantization, originally fromsignal processing, that is popular for cluster analysis in data mining,k-means clustering partitions n observations into k clusters in whicheach observation belongs to the cluster with the nearest mean, servingas a prototype of the cluster. This results in a partitioning of thedata space into Voronoi cells. A Voronoi Cell being a region within aVoronoi Diagram that is a set of points which is specified beforehand. AVoronoi Diagram is a technique of dividing space into a number ofregions k-means clustering uses cluster centers to model the data andtends to find clusters of comparable spatial extent, like K-meansclustering, but each data point has a fuzzy degree of belonging to eachseparate cluster.

An expectation-maximization process is an iterative process for findingmaximum likelihood or maximum a posteriori (MAP) estimates of parametersin statistical models, where the model depends on unobserved latentvariables. The expectation-maximization iteration alternates betweenperforming an expectation step, which creates a function for theexpectation of the log-likelihood evaluated using the current estimatefor the parameters, and a maximization step, which computes parametersmaximizing the expected log-likelihood found on the expectation step.These parameter-estimates are then used to determine the distribution ofthe latent variables in the next expectation step.

The expectation maximization process seeks to find the maximizationlikelihood expectation of the marginal likelihood by iterativelyapplying the following two steps:

1. Expectation step (E step): Calculate the expected value of the loglikelihood function, with respect to the conditional distribution of Zgiven X under the current estimate of the parameters θ^((t)):Q(θ|θ^((t)))=E _(Z|X) _(t) _(θ) _((t)) [log L(θ;X,Z]2. Maximization step (M step): Find the parameter that maximizes thisquantity:

$\theta^{({t + 1})} = {\underset{\theta}{\arg\;\max}\;{Q\left( \theta \middle| \theta^{(t)} \right)}}$

Note that in typical models to which expectation maximization isapplied:

1. The observed data points X may be discrete (taking values in a finiteor countably infinite set) or continuous (taking values in anuncountably infinite set). There may in fact be a vector of observationsassociated with each data point.

2. The missing values (a.k.a. latent variables) Z are discrete, drawnfrom a fixed number of values, and there is one latent variable perobserved data point.

3. The parameters are continuous, and are of two kinds: Parameters thatare associated with all data points, and parameters associated with aparticular value of a latent variable (i.e. associated with all datapoints whose corresponding latent variable has a particular value).

The Fourier Transform is an important image processing tool which isused to decompose an image into its sine and cosine components. Theoutput of the transformation represents the image in the Fourier orfrequency domain, while the input image is the spatial domainequivalent. In the Fourier domain image, each point represents aparticular frequency contained in the spatial domain image.

The Discrete Fourier Transform is the sampled Fourier Transform andtherefore does not contain all frequencies forming an image, but only aset of samples which is large enough to fully describe the spatialdomain image. The number of frequencies corresponds to the number ofpixels in the spatial domain image, i.e. the image in the spatial andFourier domains are of the same size.

For a square image of size N×N, the two-dimensional DFT is given by:

${F\left( {k,l} \right)} = {\sum\limits_{i = 0}^{N - 1}\;{\sum\limits_{j = 0}^{N - 1}\;{{f\left( {i,j} \right)}e^{{- i}\; 2{\pi{({\frac{k\; i}{N} + \frac{l\; j}{N}})}}}}}}$

where f(a,b) is the image in the spatial domain and the exponential termis the basis function corresponding to each point F(k,l) in the Fourierspace. The equation can be interpreted as: the value of each pointF(k,l) is obtained by multiplying the spatial image with thecorresponding base function and summing the result.

The basis functions are sine and cosine waves with increasingfrequencies, i.e. F(0,0) represents the DC-component of the image whichcorresponds to the average brightness and F(N−1,N−1) represents thehighest frequency.

A high-pass filter (HPF) is an electronic filter that passeshigh-frequency signals but attenuates (reduces the amplitude of) signalswith frequencies lower than the cutoff frequency. The actual amount ofattenuation for each frequency varies from filter to filter. A high-passfilter is usually modeled as a linear time-invariant system. A high-passfilter can also be used in conjunction with a low-pass filter to make abandpass filter. The simple first-order electronic high-pass filter isimplemented by placing an input voltage across the series combination ofa capacitor and a resistor and using the voltage across the resistor asan output. The product of the resistance and capacitance (R×C) is thetime constant (τ); the product is inversely proportional to the cutofffrequency ƒ_(c), that is:

${f_{c} = {\frac{1}{2\;\pi\;\tau} = \frac{1}{2\pi\;{RC}}}},$

-   -   where ƒ_(c) is in hertz, τ is in seconds, R is in ohms, and C is        in farads.

A low-pass filter is a filter that passes low-frequency signals andattenuates (reduces the amplitude of) signals with frequencies higherthan the cutoff frequency. The actual amount of attenuation for eachfrequency varies depending on specific filter design. Low-pass filtersare also known as high-cut filter, or treble cut filter in audioapplications. A low-pass filter is the opposite of a high-pass filter.Low-pass filters provide a smoother form of a signal, removing theshort-term fluctuations, and leaving the longer-term trend. One simplelow-pass filter circuit consists of a resistor in series with a load,and a capacitor in parallel with the load. The capacitor exhibitsreactance, and blocks low-frequency signals, forcing the low-frequencysignals through the load instead. At higher frequencies the reactancedrops, and the capacitor effectively functions as a short circuit. Thecombination of resistance and capacitance gives the time constant of thefilter. The break frequency, also called the turnover frequency orcutoff frequency (in hertz), is determined by the time constant.

A band-pass filter is a device that passes frequencies within a certainrange and attenuates frequencies outside that range. These filters canalso be created by combining a low-pass filter with a high-pass filter.Bandpass is an adjective that describes a type of filter or filteringprocess; bandpass is distinguished from passband, which refers to theactual portion of affected spectrum. Hence, a dual bandpass filter hastwo passbands. A bandpass signal is a signal containing a band offrequencies not adjacent to zero frequency, such as a signal that comesout of a bandpass filter.

FIG. 17 is a block diagram of an apparatus 1700 of variationamplification, according to an implementation. Apparatus 1700 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 1700 includes a skin-pixel-identifier1602 that identifies pixel values that are representative of the skin intwo or more images 1604. The skin-pixel-identifier 1602 performs block2502 in FIG. 25. Some implementations of the skin-pixel-identifier 1602performs an automatic seed point based clustering process on the leasttwo images 1604.

In some implementations, apparatus 1700 includes a frequency filter 1606that receives the output of the skin-pixel-identifier 1602 and applies afrequency filter to the output of the skin-pixel-identifier 1602. Thefrequency filter 1606 performs block 2504 in FIG. 25 to process theimages 1604 in the frequency domain.

In some implementations, apparatus 1700 includes a regional facialclusterial module 1608 that applies spatial clustering to the output ofthe frequency filter 1606. The regional facial clusterial module 1608performs block 2506 in FIG. 25. In some implementations the regionalfacial clusterial module 1608 includes fuzzy clustering, k-meansclustering, expectation-maximization process, Ward's apparatus or seedpoint based clustering.

In some implementations, apparatus 1700 includes a frequency-filter 1610that applies a frequency filter to the output of the regional facialclusterial module 1608, to generate a temporal variation. Thefrequency-filter 1610 performs block 2508 in FIG. 25. In someimplementations, the frequency-filter 1610 is a one-dimensional spatialFourier Transform, a high pass filter, a low pass filter, a bandpassfilter or a weighted bandpass filter. Some implementations offrequency-filter 1610 includes de-noising (e.g. smoothing of the datawith a Gaussian filter). The skin-pixel-identifier 1602, the frequencyfilter 1606, the regional facial clusterial module 1608 and thefrequency-filter 1610 amplify temporal variations in the two or moreimages 1604.

In some implementations, apparatus 1700 includes a vital-sign generator1614 that generates one or more vital sign(s) 1616 from the temporalvariation. The vital sign(s) 1616 are displayed for review by ahealthcare worker or stored in a volatile or nonvolatile memory forlater analysis, or transmitted to other devices for analysis.

FIG. 18 is a block diagram of an apparatus 1800 of variationamplification, according to an implementation. Apparatus 1800 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 1800 includes a skin-pixel-identifier1602 that identifies pixel values that are representative of the skin intwo or more images 1604. The skin-pixel-identifier 1602 performs block2502 in FIG. 25. Some implementations of the skin-pixel-identifier 1602performs an automatic seed point based clustering process on the leasttwo images 1604.

In some implementations, apparatus 1800 includes a spatial bandpassfilter 1802 that receives the output of the skin-pixel-identifier 1602and applies a spatial bandpass filter to the output of theskin-pixel-identifier 1602. The spatial bandpass filter 1802 performsblock 4702 in FIG. 47 to process the images 1604 in the spatial domain.

In some implementations, apparatus 1800 includes a regional facialclusterial module 1608 that applies spatial clustering to the output ofthe frequency filter 1606. The regional facial clusterial module 1608performs block 4704 in FIG. 47. In some implementations the regionalfacial clusterial module 1608 includes fuzzy clustering, k-meansclustering, expectation-maximization process, Ward's apparatus or seedpoint based clustering.

In some implementations, apparatus 1800 includes a temporal bandpassfilter 1804 that applies a frequency filter to the output of theregional facial clusterial module 1608. The temporal bandpass filter1804 performs block 4706 in FIG. 47. In some implementations, thetemporal bandpass filter 1804 is a one-dimensional spatial FourierTransform, a high pass filter, a low pass filter, a bandpass filter or aweighted bandpass filter. Some implementations of temporal bandpassfilter 1804 includes de-noising (e.g. smoothing of the data with aGaussian filter).

The skin-pixel-identifier 1602, the spatial bandpass filter 1802, theregional facial clusterial module 1608 and the temporal bandpass filter1804 amplify temporal variations in the two or more images 1604.

In some implementations, apparatus 1800 includes a temporal-variationidentifier 1612 that identifies temporal variation of the output of thefrequency-filter 1610. Thus, the temporal variation represents temporalvariation of the images 1604. The temporal-variation identifier 1612performs block 4708 in FIG. 47.

In some implementations, apparatus 1800 includes a vital-sign generator1614 that generates one or more vital sign(s) 1616 from the temporalvariation. The vital sign(s) 1616 are displayed for review by ahealthcare worker or stored in a volatile or nonvolatile memory forlater analysis, or transmitted to other devices for analysis.

FIG. 19 is a block diagram of an apparatus 1900 of variationamplification, according to an implementation.

In some implementations, apparatus 1900 includes a pixel-examiner 1902that examines pixel values of two or more images 1604. Thepixel-examiner 1902 performs block 4802 in FIG. 48.

In some implementations, apparatus 1900 includes a temporal variationdeterminer 1906 that determines a temporal variation of examined pixelvalues. The temporal variation determiner 1906 performs block 4804 inFIG. 48.

In some implementations, apparatus 1900 includes a signal-processor 1908that applies signal processing to the pixel value temporal variation,generating an amplified temporal variation. The signal-processor 1908performs block 4806 in FIG. 48. The signal processing amplifies thetemporal variation, even when the temporal variation is small. In someimplementations, the signal processing performed by signal-processor1908 is temporal bandpass filtering that analyzes frequencies over time.In some implementations, the signal processing performed bysignal-processor 1908 is spatial processing that removes noise.Apparatus 1900 amplifies only small temporal variations in thesignal-processing module.

In some implementations, apparatus 1800 includes a vital-sign generator1614 that generates one or more vital sign(s) 1616 from the temporalvariation. The vital sign(s) 1616 are displayed for review by ahealthcare worker or stored in a volatile or nonvolatile memory forlater analysis, or transmitted to other devices for analysis.

While apparatus 1900 can process large temporal variations, an advantagein apparatus 1900 is provided for small temporal variations. Thereforeapparatus 1900 is most effective when the two or more images 1604 havesmall temporal variations between the two or more images 1604. In someimplementations, a vital sign is generated from the amplified temporalvariations of the two or more images 1604 from the signal-processor1908.

FIG. 20 is a block diagram of an apparatus 2000 of variationamplification, according to an implementation. Apparatus 2000 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 2000 includes askin-pixel-identification module 2002 that identifies pixel values 2006that are representative of the skin in two or more images 2004. Theskin-pixel-identification module 2002 performs block 2502 in FIG. 25.Some implementations of the skin-pixel-identification module 2002perform an automatic seed point based clustering process on the leasttwo images 2004.

In some implementations, apparatus 2000 includes a frequency-filtermodule 2008 that receives the identified pixel values 2006 that arerepresentative of the skin and applies a frequency filter to theidentified pixel values 2006. The frequency-filter module 2008 performsblock 2504 in FIG. 25 to process the images 1604 in the frequencydomain. Each of the images 1604 is Fourier transformed, multiplied witha filter function and then re-transformed into the spatial domain.Frequency filtering is based on the Fourier Transform. The operatortakes an image 1604 and a filter function in the Fourier domain. Theimage 1604 is then multiplied with the filter function in apixel-by-pixel fashion using the formula:G(k,l)=F(k,l)H(k,l)

where F(k,l) is the input image 1604 of identified pixel values 2006 inthe Fourier domain, H(k,l) the filter function and G(k,l) is thefiltered image 2010. To obtain the resulting image in the spatialdomain, G(k,l) is re-transformed using the inverse Fourier Transform. Insome implementations, the frequency-filter module 2008 is atwo-dimensional spatial Fourier Transform, a high pass filter, a lowpass filter, a bandpass filter or a weighted bandpass filter.

In some implementations, apparatus 2000 includes a spatial-clustermodule 2012 that applies spatial clustering to the frequency filteredidentified pixel values of skin 2010, generating spatial clusteredfrequency filtered identified pixel values of skin 2014. Thespatial-cluster module 2012 performs block 2506 in FIG. 25. In someimplementations the spatial-cluster module 2012 includes fuzzyclustering, k-means clustering, expectation-maximization process, Ward'sapparatus or seed point based clustering.

In some implementations, apparatus 2000 includes a frequency-filtermodule 2016 that applies a frequency filter to the spatial clusteredfrequency filtered identified pixel values of skin 2014, which generatesfrequency filtered spatial clustered frequency filtered identified pixelvalues of skin 2018. The frequency-filter module 2016 performs block2508 in FIG. 25. In some implementations, the frequency-filter module2016 is a one-dimensional spatial Fourier Transform, a high pass filter,a low pass filter, a bandpass filter or a weighted bandpass filter. Someimplementations of frequency-filter module 2016 includes de-noising(e.g. smoothing of the data with a Gaussian filter).

The skin-pixel-identification module 2002, the frequency-filter module2008, the spatial-cluster module 2012 and the frequency-filter module2016 amplify temporal variations in the two or more images 1604.

In some implementations, apparatus 2000 includes a temporal-variationmodule 2020 that determines temporal variation 2022 of the frequencyfiltered spatial clustered frequency filtered identified pixel values ofskin 2018. Thus, temporal variation 2022 represents temporal variationof the images 1604. The temporal-variation module 2020 performs block2510 in FIG. 25.

FIG. 21 is a block diagram of an apparatus 2100 to generate and presentany one of a number of biological vital signs from amplified motion,according to an implementation.

In some implementations, apparatus 2100 includes a blood-flow-analyzermodule 2102 that analyzes a temporal variation to generate a pattern offlow of blood 2104. One example of the temporal variation is temporalvariation 2022 in FIG. 20. In some implementations, the pattern flow ofblood 2104 is generated from motion changes in the pixels and thetemporal variation of color changes in the skin of the images 1604. Insome implementations, apparatus 2100 includes a blood-flow displaymodule 2106 that displays the pattern of flow of blood 2104 for reviewby a healthcare worker.

In some implementations, apparatus 2100 includes a heartrate-analyzermodule 2108 that analyzes the temporal variation to generate a heartrate2110. In some implementations, the heartrate 2110 is generated from thefrequency spectrum of the temporal signal in a frequency range for heartbeats, such as (0-10 Hertz). In some implementations, apparatus 2100includes a heartrate display module 2112 that displays the heartrate2110 for review by a healthcare worker.

In some implementations, apparatus 2100 includes a respiratoryrate-analyzer module 2114 that analyzes the temporal variation todetermine a respiratory rate 2116. In some implementations, therespiratory rate 2116 is generated from the motion of the pixels in afrequency range for respiration (0-5 Hertz). In some implementations,apparatus 2100 includes respiratory rate display module 2118 thatdisplays the respiratory rate 2116 for review by a healthcare worker.

In some implementations, apparatus 2100 includes a blood-pressureanalyzer module 2120 that analyzes the temporal variation to a generateblood pressure 2122. In some implementations, the blood-pressureanalyzer module 2120 generates the blood pressure 2122 by analyzing themotion of the pixels and the color changes based on a clustering processand potentially temporal data. In some implementations, apparatus 2100includes a blood pressure display module 2124 that displays the bloodpressure 2122 for review by a healthcare worker.

In some implementations, apparatus 2100 includes an EKG analyzer module2126 that analyzes the temporal variation to generate an EKG 2128. Insome implementations, apparatus 2100 includes an EKG display module 2130that displays the EKG 2128 for review by a healthcare worker.

In some implementations, apparatus 2100 includes a pulse oximetryanalyzer module 2132 that analyzes the temporal variation to generatepulse oximetry 2134. In some implementations, the pulse oximetryanalyzer module 2132 generates the pulse oximetry 2134 by analyzing thetemporal color changes based in conjunction with the k-means clusteringprocess and potentially temporal data. In some implementations,apparatus 2100 includes a pulse oximetry display module 2136 thatdisplays the pulse oximetry 2134 for review by a healthcare worker.

FIG. 22 is a block diagram of an apparatus 2200 of variationamplification, according to an implementation. Apparatus 2200 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 2200 includes askin-pixel-identification module 2002 that identifies pixel values 2006that are representative of the skin in two or more images 1604. Theskin-pixel-identification module 2002 performs block 2502 in FIG. 25.Some implementations of the skin-pixel-identification module 2002perform an automatic seed point based clustering process on the leasttwo images 1604.

In some implementations, apparatus 2200 includes a frequency-filtermodule 2008 that receives the identified pixel values 2006 that arerepresentative of the skin and applies a frequency filter to theidentified pixel values 2006. The frequency-filter module 2008 performsblock 2504 in FIG. 25 to process the images 1604 in the frequencydomain. Each of the images 1604 is Fourier transformed, multiplied witha filter function and then re-transformed into the spatial domain.Frequency filtering is based on the Fourier Transform. The operatortakes an image 1604 and a filter function in the Fourier domain. Theimage 1604 is then multiplied with the filter function in apixel-by-pixel fashion using theG(k,l)=F(k,l)H(k,l)  formula:

where F(k,l) is the input image 1604 of identified pixel values 2006 inthe Fourier domain, H(k,l) the filter function and G(k,l) is thefiltered image 2010. To obtain the resulting image in the spatialdomain, G(k,l) is re-transformed using the inverse Fourier Transform. Insome implementations, the frequency-filter module 2008 is atwo-dimensional spatial Fourier Transform, a high pass filter, a lowpass filter, a bandpass filter or a weighted bandpass filter.

In some implementations, apparatus 2200 includes a spatial-clustermodule 2012 that applies spatial clustering to the frequency filteredidentified pixel values of skin 2010, generating spatial clusteredfrequency filtered identified pixel values of skin 2014. Thespatial-cluster module 2012 performs block 2506 in FIG. 25. In someimplementations the spatial clustering includes fuzzy clustering,k-means clustering, expectation-maximization process, Ward's apparatusor seed point based clustering.

In some implementations, apparatus 2200 includes a frequency-filtermodule 2016 that applies a frequency filter to the spatial clusteredfrequency filtered identified pixel values of skin 2014, which generatesfrequency filtered spatial clustered frequency filtered identified pixelvalues of skin 2018. The frequency-filter module 2016 performs block2508 in FIG. 25 to generate a temporal variation 2022. In someimplementations, the frequency-filter module 2016 is a one-dimensionalspatial Fourier Transform, a high pass filter, a low pass filter, abandpass filter or a weighted bandpass filter. Some implementations ofthe frequency-filter module 2016 includes de-noising (e.g. smoothing ofthe data with a Gaussian filter). The skin-pixel-identification module2002, the frequency-filter module 2008, the spatial-cluster module 2012and the frequency-filter module 2016 amplify temporal variations in thetwo or more images 1604.

The frequency-filter module 2016 is operably coupled to one of moremodules in FIG. 21 to generate and present any one or a number ofbiological vital signs from amplified motion in the temporal variation2022.

FIG. 23 is a block diagram of an apparatus 2300 of variationamplification, according to an implementation. Apparatus 2300 analyzesthe temporal and spatial variations in digital images of an animalsubject in order to generate and communicate biological vital signs.

In some implementations, apparatus 2300 includes askin-pixel-identification module 2002 that identifies pixel values 2006that are representative of the skin in two or more images 1604. Theskin-pixel-identification module 2002 performs block 2502 in FIG. 27.Some implementations of the skin-pixel-identification module 2002perform an automatic seed point based clustering process on the leasttwo images 1604. In some implementations, apparatus 2300 includes aspatial bandpass filter module 2302 that applies a spatial bandpassfilter to the identified pixel values 2006, generating spatialbandpassed filtered identified pixel values of skin 2304. In someimplementations, the spatial bandpass filter module 2302 includes atwo-dimensional spatial Fourier Transform, a high pass filter, a lowpass filter, a bandpass filter or a weighted bandpass filter. Thespatial bandpass filter module 2302 performs block 2702 in FIG. 27.

In some implementations, apparatus 2300 includes a spatial-clustermodule 2012 that applies spatial clustering to the frequency filteredidentified pixel values of skin 2010, generating spatial clusteredspatial bandpassed identified pixel values of skin 2306. In someimplementations the spatial clustering includes fuzzy clustering,k-means clustering, expectation-maximization process, Ward's apparatusor seed point based clustering. The spatial-cluster module 2012 performsblock 2704 in FIG. 27.

In some implementations, apparatus 2300 includes a temporal bandpassfilter module 2308 that applies a temporal bandpass filter to thespatial clustered spatial bandpass filtered identified pixel values ofskin 2306, generating temporal bandpass filtered spatial clusteredspatial bandpass filtered identified pixel values of skin 2310. In someimplementations, the temporal bandpass filter is a one-dimensionalspatial Fourier Transform, a high pass filter, a low pass filter, abandpass filter or a weighted bandpass filter. The temporal bandpassfilter module 2308 performs block 2706 in FIG. 27.

In some implementations, apparatus 2300 includes a temporal-variationmodule 2020 that determines temporal variation 2422 of the temporalbandpass filtered spatial clustered spatial bandpass filtered identifiedpixel values of skin 2310. Thus, temporal variation 2422 representstemporal variation of the images 1604. The temporal-variation module2420 performs block 2708 of FIG. 27. The temporal-variation module 2420is operably coupled to one or more modules in FIG. 21 to generate andpresent any one of a number of biological vital signs from amplifiedmotion in the temporal variation 2422.

FIG. 24 is a block diagram of an apparatus 2400 of variationamplification, according to an implementation.

In some implementations, apparatus 2400 includes apixel-examination-module 2402 that examines pixel values of two or moreimages 1604, generating examined pixel values 2404. Thepixel-examination-module 2402 performs block 2802 in FIG. 28.

In some implementations, apparatus 2400 includes a temporal variationdeterminer module 2406 that determines a temporal variation 2408 of theexamined pixel values 2404. The temporal variation determiner module2406 performs block 2804 in FIG. 28.

In some implementations, apparatus 2400 includes a signal-processingmodule 2410 that applies signal processing to the pixel value temporalvariations 2408, generating an amplified temporal variation 2422. Thesignal-processing module 2410 performs block 2806 in FIG. 28. The signalprocessing amplifies the temporal variation 2408, even when the temporalvariation 2408 is small. In some implementations, the signal processingperformed by signal-processing module 2410 is temporal bandpassfiltering that analyzes frequencies over time. In some implementations,the signal processing performed by signal-processing module 2410 isspatial processing that removes noise. Apparatus 2400 amplifies onlysmall temporal variations in the signal-processing module.

While apparatus 2400 can process large temporal variations, an advantagein apparatus 2400 is provided for small temporal variations. Thereforeapparatus 2400 is most effective when the two or more images 1604 havesmall temporal variations between the two or more images 1604. In someimplementations, a vital sign is generated from the amplified temporalvariations of the two or more images 1604 from the signal-processingmodule 2410.

Vital Sign Amplification Method Implementations

FIG. 25-29 each use spatial and temporal signal processing to generatevital signs from a series of digital images.

FIG. 25 is a flowchart of a method 2500 of variation amplification,according to an implementation. Method 2500 analyzes the temporal andspatial variations in digital images of an animal subject in order togenerate and communicate biological vital signs.

In some implementations, method 2500 includes identifying pixel valuesof two or more images that are representative of the skin, at block2502. Some implementations of identifying pixel values that arerepresentative of the skin includes performing an automatic seed pointbased clustering process on the least two images.

In some implementations, method 2500 includes applying a frequencyfilter to the identified pixel values that are representative of theskin, at block 2504. In some implementations, the frequency filter inblock 2504 is a two-dimensional spatial Fourier Transform, a high passfilter, a low pass filter, a bandpass filter or a weighted bandpassfilter.

In some implementations, method 2500 includes applying spatialclustering to the frequency filtered identified pixel values of skin, atblock 2506. In some implementations the spatial clustering includesfuzzy clustering, k-means clustering, expectation-maximization process,Ward's method or seed point based clustering.

In some implementations, method 2500 includes applying a frequencyfilter to the spatial clustered frequency filtered identified pixelvalues of skin, at block 2508. In some implementations, the frequencyfilter in block 2508 is a one-dimensional spatial Fourier Transform, ahigh pass filter, a low pass filter, a bandpass filter or a weightedbandpass filter. Some implementations of applying a frequency filter atblock 2508 include de-noising (e.g. smoothing of the data with aGaussian filter).

Actions 2502, 2504, 2506 and 2508 amplify temporal variations in the twoor more images.

In some implementations, method 2500 includes determining temporalvariation of the frequency filtered spatial clustered frequency filteredidentified pixel values of skin, at block 2510.

In some implementations, method 2500 includes analyzing the temporalvariation to generate a pattern of flow of blood, at block 2512. In someimplementations, the pattern flow of blood is generated from motionchanges in the pixels and the temporal variation of color changes in theskin. In some implementations, method 2500 includes displaying thepattern of flow of blood for review by a healthcare worker, at block2513.

In some implementations, method 2500 includes analyzing the temporalvariation to generate heartrate, at block 2514. In some implementations,the heartrate is generated from the frequency spectrum of the temporalvariation in a frequency range for heart beats, such as (0-10 Hertz). Insome implementations, method 2500 includes displaying the heartrate forreview by a healthcare worker, at block 2515.

In some implementations, method 2500 includes analyzing the temporalvariation to determine respiratory rate, at block 2516. In someimplementations, the respiratory rate is generated from the motion ofthe pixels in a frequency range for respiration (0-5 Hertz). In someimplementations, method 2500 includes displaying the respiratory ratefor review by a healthcare worker, at block 2517.

In some implementations, method 2500 includes analyzing the temporalvariation to generate blood pressure, at block 2518. In someimplementations, the blood pressure is generated by analyzing the motionof the pixels and the color changes based on the clustering process andpotentially temporal data from the infrared sensor. In someimplementations, method 2500 includes displaying the blood pressure forreview by a healthcare worker, at block 2519.

In some implementations, method 2500 includes analyzing the temporalvariation to generate EKG, at block 2520. In some implementations,method 2500 includes displaying the EKG for review by a healthcareworker, at block 2521.

In some implementations, method 2500 includes analyzing the temporalvariation to generate pulse oximetry, at block 2522. In someimplementations, the pulse oximetry is generated by analyzing thetemporal color changes based in conjunction with the k-means clusteringprocess and potentially temporal data from the infrared sensor. In someimplementations, method 2500 includes displaying the pulse oximetry forreview by a healthcare worker, at block 2523.

FIG. 26 is a flowchart of a method of variation amplification, accordingto an implementation that does not include a separate action ofdetermining a temporal variation. Method 2600 analyzes the temporal andspatial variations in digital images of an animal subject in order togenerate and communicate biological vital signs.

In some implementations, method 2600 includes identifying pixel valuesof two or more images that are representative of the skin, at block2502. Some implementations of identifying pixel values that arerepresentative of the skin includes performing an automatic seed pointbased clustering process on the least two images.

In some implementations, method 2600 includes applying a frequencyfilter to the identified pixel values that are representative of theskin, at block 2504. In some implementations, the frequency filter inblock 2504 is a two-dimensional spatial Fourier Transform, a high passfilter, a low pass filter, a bandpass filter or a weighted bandpassfilter.

In some implementations, method 2600 includes applying spatialclustering to the frequency filtered identified pixel values of skin, atblock 2506. In some implementations the spatial clustering includesfuzzy clustering, k-means clustering, expectation-maximization process,Ward's method or seed point based clustering.

In some implementations, method 2600 includes applying a frequencyfilter to the spatial clustered frequency filtered identified pixelvalues of skin, at block 2508, yielding a temporal variation. In someimplementations, the frequency filter in block 2508 is a one-dimensionalspatial Fourier Transform, a high pass filter, a low pass filter, abandpass filter or a weighted bandpass filter.

In some implementations, method 2600 includes analyzing the temporalvariation to generate a pattern of flow of blood, at block 2512. In someimplementations, the pattern flow of blood is generated from motionchanges in the pixels and the temporal variation of color changes in theskin. In some implementations, method 2600 includes displaying thepattern of flow of blood for review by a healthcare worker, at block2513.

In some implementations, method 2600 includes analyzing the temporalvariation to generate heartrate, at block 2514. In some implementations,the heartrate is generated from the frequency spectrum of the temporalvariation in a frequency range for heart beats, such as (0-10 Hertz). Insome implementations, method 2600 includes displaying the heartrate forreview by a healthcare worker, at block 2515.

In some implementations, method 2600 includes analyzing the temporalvariation to determine respiratory rate, at block 2516. In someimplementations, the respiratory rate is generated from the motion ofthe pixels in a frequency range for respiration (0-5 Hertz). In someimplementations, method 2600 includes displaying the respiratory ratefor review by a healthcare worker, at block 2517.

In some implementations, method 2600 includes analyzing the temporalvariation to generate blood pressure, at block 2518. In someimplementations, the blood pressure is generated by analyzing the motionof the pixels and the color changes based on the clustering process andpotentially temporal data from the infrared sensor. In someimplementations, method 2600 includes displaying the blood pressure forreview by a healthcare worker, at block 2519.

In some implementations, method 2600 includes analyzing the temporalvariation to generate EKG, at block 2520. In some implementations,method 2600 includes displaying the EKG for review by a healthcareworker, at block 2521.

In some implementations, method 2600 includes analyzing the temporalvariation to generate pulse oximetry, at block 2522. In someimplementations, the pulse oximetry is generated by analyzing thetemporal color changes based in conjunction with the k-means clusteringprocess and potentially temporal data from the infrared sensor. In someimplementations, method 2600 includes displaying the pulse oximetry forreview by a healthcare worker, at block 2523.

FIG. 27 is a flowchart of a method 2700 of variation amplification fromwhich to generate and communicate biological vital signs, according toan implementation. Method 2700 analyzes the temporal and spatialvariations in digital images of an animal subject in order to generateand communicate the biological vital signs.

In some implementations, method 2700 includes identifying pixel valuesof two or more images that are representative of the skin, at block2502. Some implementations of identifying pixel values that arerepresentative of the skin includes performing an automatic seed pointbased clustering process on the least two images.

In some implementations, method 2700 includes applying a spatialbandpass filter to the identified pixel values, at block 2702. In someimplementations, the spatial filter in block 2702 is a two-dimensionalspatial Fourier Transform, a high pass filter, a low pass filter, abandpass filter or a weighted bandpass filter.

In some implementations, method 2700 includes applying spatialclustering to the spatial bandpass filtered identified pixel values ofskin, at block 2704. In some implementations the spatial clusteringincludes fuzzy clustering, k-means clustering, expectation-maximizationprocess, Ward's method or seed point based clustering.

In some implementations, method 2700 includes applying a temporalbandpass filter to the spatial clustered spatial bandpass filteredidentified pixel values of skin, at block 2706. In some implementations,the temporal bandpass filter in block 2706 is a one-dimensional spatialFourier Transform, a high pass filter, a low pass filter, a bandpassfilter or a weighted bandpass filter.

In some implementations, method 2700 includes determining temporalvariation of the temporal bandpass filtered spatial clustered spatialbandpass filtered identified pixel values of skin, at block 2708.

In some implementations, method 2700 includes analyzing the temporalvariation to generate and visually display a pattern of flow of blood,at block 2512. In some implementations, the pattern flow of blood isgenerated from motion changes in the pixels and the temporal variationof color changes in the skin. In some implementations, method 2700includes displaying the pattern of flow of blood for review by ahealthcare worker, at block 2513.

In some implementations, method 2700 includes analyzing the temporalvariation to generate heartrate, at block 2514. In some implementations,the heartrate is generated from the frequency spectrum of the temporalvariation in a frequency range for heart beats, such as (0-10 Hertz). Insome implementations, method 2700 includes displaying the heartrate forreview by a healthcare worker, at block 2515.

In some implementations, method 2700 includes analyzing the temporalvariation to determine respiratory rate, at block 2516. In someimplementations, the respiratory rate is generated from the motion ofthe pixels in a frequency range for respiration (0-5 Hertz). In someimplementations, method 2700 includes displaying the respiratory ratefor review by a healthcare worker, at block 2517.

In some implementations, method 2700 includes analyzing the temporalvariation to generate blood pressure, at block 2518. In someimplementations, the blood pressure is generated by analyzing the motionof the pixels and the color changes based on the clustering process andpotentially temporal data from the infrared sensor. In someimplementations, method 2700 includes displaying the blood pressure forreview by a healthcare worker, at block 2519.

In some implementations, method 2700 includes analyzing the temporalvariation to generate EKG, at block 2520. In some implementations,method 2700 includes displaying the EKG for review by a healthcareworker, at block 2521.

In some implementations, method 2700 includes analyzing the temporalvariation to generate pulse oximetry, at block 2522. In someimplementations, the pulse oximetry is generated by analyzing thetemporal color changes based in conjunction with the k-means clusteringprocess and potentially temporal data from the infrared sensor. In someimplementations, method 2700 includes displaying the pulse oximetry forreview by a healthcare worker, at block 2523.

FIG. 28 is a flowchart of a method 2800 of variation amplification,according to an implementation. Method 2800 displays the temporalvariations based on temporal variations in videos that are difficult orimpossible to see with the naked eye. Method 2800 applies spatialdecomposition to a video, and applies temporal filtering to the frames.The resulting signal is then amplified to reveal hidden information.Method 2800 can visualize flow of blood filling a face in the video andalso amplify and reveal small motions, and other vital signs such asblood pressure, respiration, EKG and pulse. Method 2800 can execute inreal time to show phenomena occurring at temporal frequencies selectedby the operator. A combination of spatial and temporal processing ofvideos can amplify subtle variations that reveal important aspects ofthe world. Method 2800 considers a time series of color values at anyspatial location (e.g., a pixel) and amplifies variation in a giventemporal frequency band of interest. For example, method 2800 selectsand then amplifies a band of temporal frequencies including plausiblehuman heart rates. The amplification reveals the variation of redness asblood flows through the face. Lower spatial frequencies are temporallyfiltered (spatial pooling) to allow a subtle input signal to rise abovethe solid-state image transducer 328 and quantization noise. Thetemporal filtering approach not only amplifies color variation, but canalso reveal low-amplitude motion.

Method 2800 can enhance the subtle motions around the chest of abreathing baby. Method 2800 mathematical analysis employs a linearapproximation related to the brightness constancy assumption used inoptical flow formulations. Method 2800 also derives the conditions underwhich the linear approximation holds. The derivation leads to amultiscale approach to magnify motion without feature tracking or motionestimation. Properties of a voxel of fluid are observed, such aspressure and velocity, which evolve over time. Method 2800 studies andamplifies the variation of pixel values over time, in aspatially-multiscale manner. The spatially-multiscale manner to motionmagnification does not explicitly estimate motion, but ratherexaggerates motion by amplifying temporal color changes at fixedpositions. Method 2800 employs differential approximations that form thebasis of optical flow processes. Method 2800 described herein employslocalized spatial pooling and bandpass filtering to extract and revealvisually the signal corresponding to the pulse. The domain analysisallows amplification and visualization of the pulse signal at eachlocation on the face. Asymmetry in facial blood flow can be a symptom ofarterial problems.

Method 2800 described herein makes imperceptible motions visible using amultiscale approach. Method 2800 amplifies small motions, in oneembodiment. Nearly invisible changes in a dynamic environment can berevealed through spatio-temporal processing of standard monocular videosequences. Moreover, for a range of amplification values that issuitable for various applications, explicit motion estimation is notrequired to amplify motion in natural videos. Method 2800 is well suitedto small displacements and lower spatial frequencies. Single frameworkcan amplify both spatial motion and purely temporal changes (e.g., aheart pulse) and can be adjusted to amplify particular temporalfrequencies. A spatial decomposition module decomposes the input videointo different spatial frequency bands, then applies the same temporalfilter to the spatial frequency bands. The outputted filtered spatialbands are then amplified by an amplification factor, added back to theoriginal signal by adders, and collapsed by a reconstruction module togenerate the output video. The temporal filter and amplification factorscan be tuned to support different applications. For example, the systemcan reveal unseen motions of a solid-state image transducer 328, causedby the flipping mirror during a photo burst.

Method 2800 combines spatial and temporal processing to emphasize subtletemporal changes in a video. Method 2800 decomposes the video sequenceinto different spatial frequency bands. These bands might be magnifieddifferently because (a) the bands might exhibit differentsignal-to-noise ratios or (b) the bands might contain spatialfrequencies for which the linear approximation used in motionmagnification does not hold. In the latter case, method 2800 reduces theamplification for these bands to suppress artifacts. When the goal ofspatial processing is to increase temporal signal-to-noise ratio bypooling multiple pixels, the method spatially low-pass filters theframes of the video and downsamples the video frames for computationalefficiency. In the general case, however, method 2800 computes a fullLaplacian pyramid.

Method 2800 then performs temporal processing on each spatial band.Method 2800 considers the time series corresponding to the value of apixel in a frequency band and applies a bandpass filter to extract thefrequency bands of interest. As one example, method 2800 may selectfrequencies within the range of 0.4-4 Hz, corresponding to 24-240 beatsper minute, if the operator wants to magnify a pulse. If method 2800extracts the pulse rate, then method 2800 can employ a narrow frequencyband around that value. The temporal processing is uniform for allspatial levels and for all pixels within each level. Method 2800 thenmultiplies the extracted bandpassed signal by a magnification factor.alpha. The magnification factor .alpha. can be specified by theoperator, and can be attenuated automatically. Method 2800 adds themagnified signal to the original signal and collapses the spatialpyramid to obtain the final output. Since natural videos are spatiallyand temporally smooth, and since the filtering is performed uniformlyover the pixels, the method implicitly maintains spatiotemporalcoherency of the results. The motion magnification amplifies smallmotion without tracking motion. Temporal processing produces motionmagnification, shown using an analysis that relies on the first-orderTaylor series expansions common in optical flow analyses.

Method 2800 begins with a pixel-examination module in the microprocessor302 of the non-touch biologic detectors 300, 400 or 300 examining pixelvalues of two or more images 1604 from the solid-state image transducer328, at block 2802.

Method 2800 thereafter determines the temporal variation of the examinedpixel values, at block 2804 by a temporal-variation module in themicroprocessor 302.

A signal-processing module in the microprocessor 302 applies signalprocessing to the pixel value temporal variations, at block 2806. Signalprocessing amplifies the determined temporal variations, even when thetemporal variations are small. Method 2800 amplifies only small temporalvariations in the signal-processing module. While method 2800 can beapplied to large temporal variations, an advantage in method 2800 isprovided for small temporal variations. Therefore method 2800 is mosteffective when the input images 1604 have small temporal variationsbetween the images 1604. In some implementations, the signal processingat block 2806 is temporal bandpass filtering that analyzes frequenciesover time. In some implementations, the signal processing at block 2806is spatial processing that removes noise.

In some implementations, a vital sign is generated from the amplifiedtemporal variations of the input images 1604 from the signal processorat block 2808. Examples of generating a vital signal from a temporalvariation include as in actions 2512, 2514, 2516, 2518, 2520 and 2522 inFIGS. 25, 26 and 27.

FIG. 29 is a flowchart of a method 2900 of variation amplification fromwhich to generate and communicate biological vital signs, according toan implementation. Method 2900 analyzes the temporal and spatialvariations in digital images of an animal subject in order to generateand communicate the biological vital signs.

In some implementations, method 2900 includes cropping at least twoimages to exclude areas that do not include a skin region, at block2902. For example, the excluded area can be a perimeter area around thecenter of each image, so that an outside border area of the image isexcluded. In some implementations of cropping out the border, about 72%of the width and about 72% of the height of each image is cropped out,leaving only 7.8% of the original uncropped image, which eliminatesabout 11/12 of each image and reduces the amount of processing time forthe remainder of the actions in this process by about 12-fold. This oneaction alone at block 2902 in method 2900 can reduce the processing timeof plurality of images 330 in comparison to method 2700 from 4 minutesto 30 seconds, which is of significant difference to the health workerswho used devices that implement method 2900. In some implementations,the remaining area of the image after cropping in a square area and inother implementation the remaining area after cropping is a circulararea. Depending upon the topography and shape of the area in the imagesthat has the most pertinent portion of the imaged subject, differentgeometries and sizes are most beneficial. The action of cropping theimages at block 2902 can be applied at the beginning of methods 2500,2600, 2700 and 2800 in FIGS. 25, 26, 27 and 28, respectively. In otherimplementations of apparatus 1600, 1700, 1800, 1900, 2000, 2100, 2200,2300 and 2400, a cropper module that performs block 2902 is placed atthe beginning of the modules to greatly decrease processing time of theapparatus.

In some implementations, method 2900 includes identifying pixel valuesof the at least two or more cropped images that are representative ofthe skin, at block 2904. Some implementations of identifying pixelvalues that are representative of the skin include performing anautomatic seed point based clustering process on the least two images.

In some implementations, method 2900 includes applying a spatialbandpass filter to the identified pixel values, at block 2702. In someimplementations, the spatial filter in block 2702 is a two-dimensionalspatial Fourier Transform, a high pass filter, a low pass filter, abandpass filter or a weighted bandpass filter.

In some implementations, method 2900 includes applying spatialclustering to the spatial bandpass filtered identified pixel values ofskin, at block 2704. In some implementations the spatial clusteringincludes fuzzy clustering, k-means clustering, expectation-maximizationprocess, Ward's method or seed point based clustering.

In some implementations, method 2900 includes applying a temporalbandpass filter to the spatial clustered spatial bandpass filteredidentified pixel values of skin, at block 2706. In some implementations,the temporal bandpass filter in block 2706 is a one-dimensional spatialFourier Transform, a high pass filter, a low pass filter, a bandpassfilter or a weighted bandpass filter.

In some implementations, method 2900 includes determining temporalvariation of the temporal bandpass filtered spatial clustered spatialbandpass filtered identified pixel values of skin, at block 2708.

In some implementations, method 2900 includes analyzing the temporalvariation to generate and visually display a pattern of flow of blood,at block 2512. In some implementations, the pattern flow of blood isgenerated from motion changes in the pixels and the temporal variationof color changes in the skin. In some implementations, method 2900includes displaying the pattern of flow of blood for review by ahealthcare worker, at block 2513.

In some implementations, method 2900 includes analyzing the temporalvariation to generate heartrate, at block 2514. In some implementations,the heartrate is generated from the frequency spectrum of the temporalvariation in a frequency range for heart beats, such as (0-10 Hertz). Insome implementations, method 2900 includes displaying the heartrate forreview by a healthcare worker, at block 2515.

In some implementations, method 2900 includes analyzing the temporalvariation to determine respiratory rate, at block 2516. In someimplementations, the respiratory rate is generated from the motion ofthe pixels in a frequency range for respiration (0-5 Hertz). In someimplementations, method 2900 includes displaying the respiratory ratefor review by a healthcare worker, at block 2517.

In some implementations, method 2900 includes analyzing the temporalvariation to generate blood pressure, at block 2518. In someimplementations, the blood pressure is generated by analyzing the motionof the pixels and the color changes based on the clustering process andpotentially temporal data from the infrared sensor. In someimplementations, method 2900 includes displaying the blood pressure forreview by a healthcare worker, at block 2519.

In some implementations, method 2900 includes analyzing the temporalvariation to generate EKG, at block 2520. In some implementations,method 2900 includes displaying the EKG for review by a healthcareworker, at block 2521.

In some implementations, method 2900 includes analyzing the temporalvariation to generate pulse oximetry, at block 2522. In someimplementations, the pulse oximetry is generated by analyzing thetemporal color changes based in conjunction with the k-means clusteringprocess and potentially temporal data from the infrared sensor. In someimplementations, method 2900 includes displaying the pulse oximetry forreview by a healthcare worker, at block 2523.

Non-Touch Cubic Temperature Estimation Method Implementations

FIG. 30 is a flowchart of a method 3000 to estimate a body coretemperature from an external source point in reference to a cubicrelationship, according to an implementation.

Method 3000 includes receiving from a non-touch electromagnetic sensor anumerical representation of electromagnetic energy of the externalsource point of a subject, at block 3002.

Method 3000 also includes estimating the body core temperature of thesubject from the numerical representation of the electromagnetic energyof the external source point, a representation of an ambient airtemperature reading, a representation of a calibration difference, and arepresentation of a bias in consideration of the temperature sensingmode, at block 3004. The estimating at block 3004 is based on a cubicrelationship representing three thermal ranges between the body coretemperature and the numerical representation of the electromagneticenergy of the external source point. The cubic relationship includes acoefficient representative of different relationships between theexternal source point and the body core temperature in the three thermalranges.

A cubic relationship for all ranges of ambient temperatures providesbest results because a linear or a quadratic relationship provideinaccurate estimates of body temperature, yet a quartic relationship, aquintic relationship, sextic relationship, a septic relationship or anoctic relationship provide estimates along a highly irregular curve thatis far too wavy or twisting with relatively sharp deviations from oneambient temperature to another ambient temperature.

Method 3000 also includes displaying the body core temperature, at block3006.

FIG. 31 is a flowchart of a method 3100 to estimate a body coretemperature from an external source point and other measurements inreference to a cubic relationship, according to an implementation;

Method 3100 includes receiving from a non-touch electromagnetic sensor anumerical representation of electromagnetic energy of the externalsource point of a subject, at block 3002.

Method 3100 also includes estimating the body core temperature of thesubject from the numerical representation of the electromagnetic energyof the external source point, a representation of an ambient airtemperature reading, a representation of a calibration difference, and arepresentation of a bias in consideration of the temperature sensingmode, at block 3102. The estimating at block 3104 is based on a cubicrelationship representing three thermal ranges between the body coretemperature and the numerical representation of the electromagneticenergy of the external source point. The cubic relationship includes acoefficient representative of different relationships between theexternal source point and the body core temperature in the three thermalranges, wherein the cubic relationship is:T _(B) =A _(Skin) ³ +BT _(Skin) ² +CT _(Skin) +D−E(T _(Ambient)−75),T_(Ambient) <T ₁ or T _(Ambient) >T ₂ and T _(B) =AT _(Skin) ³ +BT_(Skin) ² +CT _(Skin) +D,T ₁ <T _(Ambient) <T ₂

where:

-   -   T_(B) is the body core temperature    -   T_(skin) is the numerical representation of the electromagnetic        energy of the external source point    -   A is 0.0002299688    -   B is −0.0464237524    -   C is 3.05944877    -   D is 31.36205    -   E is 0.135    -   T_(ambient) is the ambient air temperature    -   T₁ and T₂ are boundaries between the three thermal ranges    -   T₁ and T₂ are selected from a group of pairs of ambient        temperatures consisting of 67° F. and 82° F.; 87° F. and 95° F.;        and 86° F. and 101° F.

Method 3100 also includes displaying the body core temperature, at block3006.

In some implementations, methods 2500-3100 are implemented as a sequenceof instructions which, when executed by a microprocessor 302 in FIG.3-12, microprocessor 3504 In FIG. 35, main processor 3202 in FIG. 32 orprocessing unit 3304 in FIG. 33, cause the processor to perform therespective method. In other implementations, methods 2500-3100 areimplemented as a computer-accessible medium having computer executableinstructions capable of directing a microprocessor, such asmicroprocessor 302 in FIG. 3-12, microprocessor 3504 in FIG. 35, mainprocessor 3202 in FIG. 32 or processing unit 3304 in FIG. 33, to performthe respective method. In different implementations, the medium is amagnetic medium, an electronic medium, or an optical medium.

Hardware and Operating Environments

FIG. 32 is a block diagram of a hand-held device 3200, according to animplementation. The hand-held device 3200 may also have the capabilityto allow voice communication. Depending on the functionality provided bythe hand-held device 3200, the hand-held device 3200 may be referred toas a data messaging device, a two-way pager, a cellular telephone withdata messaging capabilities, a wireless Internet appliance, or a datacommunication device (with or without telephony capabilities).

The hand-held device 3200 includes a number of modules such as a mainprocessor 3202 that controls the overall operation of the hand-helddevice 3200. Communication functions, including data and voicecommunications, are performed through a communication subsystem 3204.The communication subsystem 3204 receives messages from and sendsmessages to wireless networks 3205. In other implementations of thehand-held device 3200, the communication subsystem 3204 can beconfigured in accordance with the Global System for Mobile Communication(GSM), General Packet Radio Services (GPRS), Enhanced Data GSMEnvironment (EDGE), Universal Mobile Telecommunications Service (UMTS),data-centric wireless networks, voice-centric wireless networks, anddual-mode networks that can support both voice and data communicationsover the same physical base stations. Combined dual-mode networksinclude, but are not limited to, Code Division Multiple Access (CDMA) orCDMA2000 networks, GSM/GPRS networks (as mentioned above), and futurethird-generation (3G) networks like EDGE and UMTS. Some other examplesof data-centric networks include Mobitex™ and DataTAC™ networkcommunication systems. Examples of other voice-centric data networksinclude Personal Communication Systems (PCS) networks like GSM and TimeDivision Multiple Access (TDMA) systems.

The wireless link connecting the communication subsystem 3204 with thewireless network 3205 represents one or more different Radio Frequency(RF) channels. With newer network protocols, these channels are capableof supporting both circuit switched voice communications and packetswitched data communications.

The main processor 3202 also interacts with additional subsystems suchas a Random Access Memory (RAM) 3206, a flash memory 3208, a display3210, an auxiliary input/output (I/O) subsystem 3212, a data port 3214,a keyboard 3216, a speaker 3218, a microphone 3220, short-rangecommunications subsystem 3222 and other device subsystems 3224. In someimplementations, the flash memory 3208 includes a hybrid femtocell/Wi-Fiprotocol stack 3209. The stack 3209 supports authentication andauthorization between the hand-held device 3200 into a shared Wi-Finetwork and both a 3G and 4G mobile networks.

Some of the subsystems of the hand-held device 3200 performcommunication-related functions, whereas other subsystems may provide“resident” or on-device functions. By way of example, the display 3210and the keyboard 3216 may be used for both communication-relatedfunctions, such as entering a text message for transmission over thewireless network 3205, and device-resident functions such as acalculator or task list.

The hand-held device 3200 can transmit and receive communication signalsover the wireless network 3205 after required network registration oractivation procedures have been completed. Network access is associatedwith a subscriber or user of the hand-held device 3200. To identify asubscriber, the hand-held device 3200 requires a SIM/RUIM card 3226(i.e. Subscriber Identity Module or a Removable User Identity Module) tobe inserted into a SIM/RUIM interface 3228 in order to communicate witha network. The SIM card or RUIM 3226 is one type of a conventional“smart card” that can be used to identify a subscriber of the hand-helddevice 3200 and to personalize the hand-held device 3200, among otherthings. Without the SIM card 3226, the hand-held device 3200 is notfully operational for communication with the wireless network 3205. Byinserting the SIM card/RUIM 3226 into the SIM/RUIM interface 3228, asubscriber can access all subscribed services. Services may include: webbrowsing and messaging such as e-mail, voice mail, Short Message Service(SMS), and Multimedia Messaging Services (MMS). More advanced servicesmay include: point of sale, field service and sales force automation.The SIM card/RUIM 3226 includes a processor and memory for storinginformation. Once the SIM card/RUIM 3226 is inserted into the SIM/RUIMinterface 3228, the SIM is coupled to the main processor 3202. In orderto identify the subscriber, the SIM card/RUIM 3226 can include some userparameters such as an International Mobile Subscriber Identity (IMSI).An advantage of using the SIM card/RUIM 3226 is that a subscriber is notnecessarily bound by any single physical mobile device. The SIMcard/RUIM 3226 may store additional subscriber information for thehand-held device 3200 as well, including datebook (or calendar)information and recent call information. Alternatively, useridentification information can also be programmed into the flash memory3208.

The hand-held device 3200 is a battery-powered device and includes abattery interface 3232 for receiving one or more rechargeable batteries3230. In one or more implementations, the battery 3230 can be a smartbattery with an embedded microprocessor. The battery interface 3232 iscoupled to a regulator 3233, which assists the battery 3230 in providingpower V+ to the hand-held device 3200. Although current technology makesuse of a battery, future technologies such as micro fuel cells mayprovide the power to the hand-held device 3200.

The hand-held device 3200 also includes an operating system 3234 andmodules 3236 to 3249 which are described in more detail below. Theoperating system 3234 and the modules 3236 to 3249 that are executed bythe main processor 3202 are typically stored in a persistent nonvolatilemedium such as the flash memory 3208, which may alternatively be aread-only memory (ROM) or similar storage element (not shown). Thoseskilled in the art will appreciate that portions of the operating system3234 and the modules 3236 to 3249, such as specific device applications,or parts thereof, may be temporarily loaded into a volatile store suchas the RAM 3206. Other modules can also be included.

The subset of modules 3236 that control basic device operations,including data and voice communication applications, will normally beinstalled on the hand-held device 3200 during its manufacture. Othermodules include a message application 3238 that can be any suitablemodule that allows a user of the hand-held device 3200 to transmit andreceive electronic messages. Various alternatives exist for the messageapplication 3238 as is well known to those skilled in the art. Messagesthat have been sent or received by the user are typically stored in theflash memory 3208 of the hand-held device 3200 or some other suitablestorage element in the hand-held device 3200. In one or moreimplementations, some of the sent and received messages may be storedremotely from the hand-held device 3200 such as in a data store of anassociated host system with which the hand-held device 3200communicates.

The modules can further include a device state module 3240, a PersonalInformation Manager (PIM) 3242, and other suitable modules (not shown).The device state module 3240 provides persistence, i.e. the device statemodule 3240 ensures that important device data is stored in persistentmemory, such as the flash memory 3208, so that the data is not lost whenthe hand-held device 3200 is turned off or loses power.

The PIM 3242 includes functionality for organizing and managing dataitems of interest to the user, such as, but not limited to, e-mail,contacts, calendar events, voice mails, appointments, and task items. APIM application has the ability to transmit and receive data items viathe wireless network 3205. PIM data items may be seamlessly integrated,synchronized, and updated via the wireless network 3205 with thehand-held device 3200 subscriber's corresponding data items storedand/or associated with a host computer system. This functionalitycreates a mirrored host computer on the hand-held device 3200 withrespect to such items. This can be particularly advantageous when thehost computer system is the hand-held device 3200 subscriber's officecomputer system.

The hand-held device 3200 also includes a connect module 3244, and an ITpolicy module 3246. The connect module 3244 implements the communicationprotocols that are required for the hand-held device 3200 to communicatewith the wireless infrastructure and any host system, such as anenterprise system, with which the hand-held device 3200 is authorized tointerface. Examples of a wireless infrastructure and an enterprisesystem are given in FIGS. 32 and 33, which are described in more detailbelow.

The connect module 3244 includes a set of APIs that can be integratedwith the hand-held device 3200 to allow the hand-held device 3200 to useany number of services associated with the enterprise system. Theconnect module 3244 allows the hand-held device 3200 to establish anend-to-end secure, authenticated communication pipe with the hostsystem. A subset of applications for which access is provided by theconnect module 3244 can be used to pass IT policy commands from the hostsystem to the hand-held device 3200. This can be done in a wireless orwired manner. These instructions can then be passed to the IT policymodule 3246 to modify the configuration of the hand-held device 3200.Alternatively, in some cases, the IT policy update can also be done overa wired connection.

The IT policy module 3246 receives IT policy data that encodes the ITpolicy. The IT policy module 3246 then ensures that the IT policy datais authenticated by the hand-held device 3200. The IT policy data canthen be stored in the flash memory 3206 in its native form. After the ITpolicy data is stored, a global notification can be sent by the ITpolicy module 3246 to all of the applications residing on the hand-helddevice 3200. Applications for which the IT policy may be applicable thenrespond by reading the IT policy data to look for IT policy rules thatare applicable.

The IT policy module 3246 can include a parser 3247, which can be usedby the applications to read the IT policy rules. In some cases, anothermodule or application can provide the parser. Grouped IT policy rules,described in more detail below, are retrieved as byte streams, which arethen sent (recursively) into the parser to determine the values of eachIT policy rule defined within the grouped IT policy rule. In one or moreimplementations, the IT policy module 3246 can determine whichapplications are affected by the IT policy data and transmit anotification to only those applications. In either of these cases, forapplications that are not being executed by the main processor 3202 atthe time of the notification, the applications can call the parser orthe IT policy module 3246 when the applications are executed todetermine if there are any relevant IT policy rules in the newlyreceived IT policy data.

All applications that support rules in the IT Policy are coded to knowthe type of data to expect. For example, the value that is set for the“WEP User Name” IT policy rule is known to be a string; therefore thevalue in the IT policy data that corresponds to this rule is interpretedas a string. As another example, the setting for the “Set MaximumPassword Attempts” IT policy rule is known to be an integer, andtherefore the value in the IT policy data that corresponds to this ruleis interpreted as such.

After the IT policy rules have been applied to the applicableapplications or configuration files, the IT policy module 3246 sends anacknowledgement back to the host system to indicate that the IT policydata was received and successfully applied.

The programs 3237 can also include a temporal-variation-amplifier 3248and a vital sign generator 3249. In some implementations, thetemporal-variation-amplifier 3248 includes a skin-pixel-identifier 1602,a frequency-filter 1606, a regional facial clusterial module 1608 and afrequency filter 1610 as in FIGS. 16 and 17. In some implementations,the temporal-variation-amplifier 3248 includes a skin-pixel-identifier1602, a spatial bandpass-filter 1802, regional facial clusterial module1608 and a temporal bandpass filter 1804 as in FIG. 18. In someimplementations, the temporal-variation-amplifier 3248 includes apixel-examiner 1902, a temporal variation determiner 1906 and signalprocessor 1908 as in FIG. 19. In some implementations, thetemporal-variation-amplifier 3248 includes a skin-pixel-identificationmodule 2002, a frequency-filter module 2008, spatial-cluster module 2012and a frequency filter module 2016 as in FIGS. 20 and 21. In someimplementations, the temporal-variation-amplifier module 2002, a spatialbandpass filter module 2302, a spatial-cluster module 2012 and atemporal bandpass filter module 2306 as in FIG. 23. In someimplementations, the temporal-variation-amplifier 3248 includes apixel-examination-module 2402, a temporal variation determiner module2406 and a signal processing module 2410 as in FIG. 24. The solid-stateimage transducer 328 captures images 330 and the vital sign generator3249 generates the vital sign(s) 1616 that is displayed by display 3210or transmitted by communication subsystem 3204 or short-rangecommunications subsystem 3222, enunciated by speaker 3218 or stored byflash memory 3208.

Other types of modules can also be installed on the hand-held device3200. These modules can be third party modules, which are added afterthe manufacture of the hand-held device 3200. Examples of third partyapplications include games, calculators, utilities, etc.

The additional applications can be loaded onto the hand-held device 3200through at least one of the wireless network 3205, the auxiliary I/Osubsystem 3212, the data port 3214, the short-range communicationssubsystem 3222, or any other suitable device subsystem 3224. Thisflexibility in application installation increases the functionality ofthe hand-held device 3200 and may provide enhanced on-device functions,communication-related functions, or both. For example, securecommunication applications may enable electronic commerce functions andother such financial transactions to be performed using the hand-helddevice 3200.

The data port 3214 enables a subscriber to set preferences through anexternal device or module and extends the capabilities of the hand-helddevice 3200 by providing for information or module downloads to thehand-held device 3200 other than through a wireless communicationnetwork. The alternate download path may, for example, be used to loadan encryption key onto the hand-held device 3200 through a direct andthus reliable and trusted connection to provide secure devicecommunication.

The data port 3214 can be any suitable port that enables datacommunication between the hand-held device 3200 and another computingdevice. The data port 3214 can be a serial or a parallel port. In someinstances, the data port 3214 can be a USB port that includes data linesfor data transfer and a supply line that can provide a charging currentto charge the battery 3230 of the hand-held device 3200.

The short-range communications subsystem 3222 provides for communicationbetween the hand-held device 3200 and different systems or devices,without the use of the wireless network 3205. For example, the subsystem3222 may include an infrared device and associated circuits and modulesfor short-range communication. Examples of short-range communicationstandards include standards developed by the Infrared Data Association(IrDA), Bluetooth, and the 802.11 family of standards developed by IEEE.

Bluetooth is a wireless technology standard for exchanging data overshort distances (using short-wavelength radio transmissions in the ISMband from 2400-2480 MHz) from fixed and mobile devices, creatingpersonal area networks (PANs) with high levels of security. Created bytelecom vendor Ericsson in 2894, Bluetooth was originally conceived as awireless alternative to RS-232 data cables. Blutooth can connect severaldevices, overcoming problems of synchronization. Bluetooth operates inthe range of 2400-2483.5 MHz (including guard bands), which is in theglobally unlicensed Industrial, Scientific and Medical (ISM) 2.4 GHzshort-range radio frequency band. Bluetooth uses a radio technologycalled frequency-hopping spread spectrum. The transmitted data isdivided into packets and each packet is transmitted on one of the 79designated Bluetooth channels. Each channel has a bandwidth of 1 MHz.The first channel starts at 2402 MHz and continues up to 2480 MHz in 1MHz steps. The first channel usually performs 1600 hops per second, withAdaptive Frequency-Hopping (AFH) enabled. Originally Gaussianfrequency-shift keying (GFSK) modulation was the only modulation schemeavailable; subsequently, since the introduction of Bluetooth 2.0+EDR,π/4-DQPSK and 8DPSK modulation may also be used between compatibledevices. Devices functioning with GFSK are said to be operating in basicrate (BR) mode where an instantaneous data rate of 1 Mbit/s is possible.The term Enhanced Data Rate (EDR) is used to describe π/4-DPSK and 8DPSKschemes, each giving 2 and 3 Mbit/s respectively. The combination ofthese (BR and EDR) modes in Bluetooth radio technology is classified asa “BR/EDR radio”. Bluetooth is a packet-based protocol with amaster-slave structure. One master may communicate with up to 7 slavesin a piconet; all devices share the master's clock. Packet exchange isbased on the basic clock, defined by the master, which ticks at 312.5 μsintervals. Two clock ticks make up a slot of 625 μs; two slots make up aslot pair of 1250 μs. In the simple case of single-slot packets themaster transmits in even slots and receives in odd slots; the slave,conversely, receives in even slots and transmits in odd slots. Packetsmay be 1, 3 or 5 slots long but in all cases the master transmit willbegin in even slots and the slave transmit in odd slots. A masterBluetooth device can communicate with a maximum of seven devices in apiconet (an ad-hoc computer network using Bluetooth technology), thoughnot all devices reach this maximum. The devices can switch roles, byagreement, and the slave can become the master (for example, a headsetinitiating a connection to a phone will necessarily begin as master, asinitiator of the connection; but may subsequently prefer to be slave).The Bluetooth Core Specification provides for the connection of two ormore piconets to form a scatternet, in which certain devicessimultaneously play the master role in one piconet and the slave role inanother. At any given time, data can be transferred between the masterand one other device (except for the little-used broadcast mode. Themaster chooses which slave device to address; typically, the masterswitches rapidly from one device to another in a round-robin fashion.Since the master chooses which slave to address, whereas a slave is (intheory) supposed to listen in each receive slot, being a master is alighter burden than being a slave. Being a master of seven slaves ispossible; being a slave of more than one master is difficult. Many ofthe services offered over Bluetooth can expose private data or allow theconnecting party to control the Bluetooth device. For security reasonsit is necessary to be able to recognize specific devices and thus enablecontrol over which devices are allowed to connect to a given Bluetoothdevice. At the same time, it is useful for Bluetooth devices to be ableto establish a connection without user intervention (for example, assoon as the Bluetooth devices of each other are in range). To resolvethis conflict, Bluetooth uses a process called bonding, and a bond iscreated through a process called pairing. The pairing process istriggered either by a specific request from a user to create a bond (forexample, the user explicitly requests to “Add a Bluetooth device”), orthe pairing process is triggered automatically when connecting to aservice where (for the first time) the identity of a device is requiredfor security purposes. These two cases are referred to as dedicatedbonding and general bonding respectively. Pairing often involves somelevel of user interaction; this user interaction is the basis forconfirming the identity of the devices. Once pairing successfullycompletes, a bond will have been formed between the two devices,enabling those two devices to connect to each other in the futurewithout requiring the pairing process in order to confirm the identityof the devices. When desired, the bonding relationship can later beremoved by the user. Secure Simple Pairing (SSP): This is required byBluetooth v2.1, although a Bluetooth v2.1 device may only use legacypairing to interoperate with a v2.0 or earlier device. Secure SimplePairing uses a form of public key cryptography, and some types can helpprotect against man in the middle, or MITM attacks. SSP has thefollowing characteristics: Just works: As implied by the name, thismethod just works. No user interaction is required; however, a devicemay prompt the user to confirm the pairing process. This method istypically used by headsets with very limited IO capabilities, and ismore secure than the fixed PIN mechanism which is typically used forlegacy pairing by this set of limited devices. This method provides noman in the middle (MITM) protection. Numeric comparison: If both deviceshave a display and at least one can accept a binary Yes/No user input,both devices may use Numeric Comparison. This method displays a 6-digitnumeric code on each device. The user should compare the numbers toensure that the numbers are identical. If the comparison succeeds, theuser(s) should confirm pairing on the device(s) that can accept aninput. This method provides MITM protection, assuming the user confirmson both devices and actually performs the comparison properly. PasskeyEntry: This method may be used between a device with a display and adevice with numeric keypad entry (such as a keyboard), or two deviceswith numeric keypad entry. In the first case, the display is used toshow a 6-digit numeric code to the user, who then enters the code on thekeypad. In the second case, the user of each device enters the same6-digit number. Both of these cases provide MITM protection. Out of band(OOB): This method uses an external means of communication, such as NearField Communication (NFC) to exchange some information used in thepairing process. Pairing is completed using the Bluetooth radio, butrequires information from the OOB mechanism. This provides only thelevel of MITM protection that is present in the OOB mechanism. SSP isconsidered simple for the following reasons: In most cases, SSP does notrequire a user to generate a passkey. For use-cases not requiring MITMprotection, user interaction can be eliminated. For numeric comparison,MITM protection can be achieved with a simple equality comparison by theuser. Using OOB with NFC enables pairing when devices simply get close,rather than requiring a lengthy discovery process.

In use, a received signal such as a text message, an e-mail message, orweb page download will be processed by the communication subsystem 3204and input to the main processor 3202. The main processor 3202 will thenprocess the received signal for output to the display 3210 oralternatively to the auxiliary I/O subsystem 3212. A subscriber may alsocompose data items, such as e-mail messages, for example, using thekeyboard 3216 in conjunction with the display 3210 and possibly theauxiliary I/O subsystem 3212. The auxiliary subsystem 3212 may includedevices such as: a touch screen, mouse, track ball, infrared fingerprintdetector, or a roller wheel with dynamic button pressing capability. Thekeyboard 3216 is preferably an alphanumeric keyboard and/ortelephone-type keypad. However, other types of keyboards may also beused. A composed item may be transmitted over the wireless network 3205through the communication subsystem 3204.

For voice communications, the overall operation of the hand-held device3200 is substantially similar, except that the received signals areoutput to the speaker 3218, and signals for transmission are generatedby the microphone 3220. Alternative voice or audio I/O subsystems, suchas a voice message recording subsystem, can also be implemented on thehand-held device 3200. Although voice or audio signal output isaccomplished primarily through the speaker 3218, the display 3210 canalso be used to provide additional information such as the identity of acalling party, duration of a voice call, or other voice call relatedinformation.

FIG. 33 is a block diagram of a hardware and operating environment 3300in which different implementations can be practiced. The description ofFIG. 33 provides an overview of computer hardware and a suitablecomputing environment in conjunction with which some implementations canbe implemented. Implementations are described in terms of a computerexecuting computer-executable instructions. However, someimplementations can be implemented entirely in computer hardware inwhich the computer-executable instructions are implemented in read-onlymemory. Some implementations can also be implemented in client/servercomputing environments where remote devices that perform tasks arelinked through a communications network. Program modules can be locatedin both local and remote memory storage devices in a distributedcomputing environment.

FIG. 33 illustrates an example of a computer environment 3300 useful inthe context of the environment of FIG. 3-18, in accordance with animplementation. The computer environment 3300 includes a computationresource 3302 capable of implementing the processes described herein. Itwill be appreciated that other devices can alternatively used thatinclude more modules, or fewer modules, than those illustrated in FIG.33.

The illustrated operating environment 3300 is only one example of asuitable operating environment, and the example described with referenceto FIG. 33 is not intended to suggest any limitation as to the scope ofuse or functionality of the implementations of this disclosure. Otherwell-known computing systems, environments, and/or configurations can besuitable for implementation and/or application of the subject matterdisclosed herein.

The computation resource 3302 includes one or more processors orprocessing units 3304, a system memory 3306, and a bus 3308 that couplesvarious system modules including the system memory 3306 to processingunit 3304 and other elements in the environment 3300. The bus 3308represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port and a processor or local bus using any of avariety of bus architectures, and can be compatible with SCSI (smallcomputer system interconnect), or other conventional bus architecturesand protocols.

The system memory 3306 includes nonvolatile read-only memory (ROM) 3310and random access memory (RAM) 3312, which can or can not includevolatile memory elements. A basic input/output system (BIOS) 3314,containing the elementary routines that help to transfer informationbetween elements within computation resource 3302 and with externalitems, typically invoked into operating memory during start-up, isstored in ROM 3310.

The computation resource 3302 further can include a non-volatileread/write memory 3316, represented in FIG. 33 as a hard disk drive,coupled to bus 3308 via a data media interface 3317 (e.g., a SCSI, ATA,or other type of interface); a magnetic disk drive (not shown) forreading from, and/or writing to, a removable magnetic disk 3320 and anoptical disk drive (not shown) for reading from, and/or writing to, aremovable optical disk 3326 such as a CD, DVD, or other optical media.

The non-volatile read/write memory 3316 and associated computer-readablemedia provide nonvolatile storage of computer-readable instructions,data structures, program modules and other data for the computationresource 3302. Although the exemplary environment 3300 is describedherein as employing a non-volatile read/write memory 3316, a removablemagnetic disk 3320 and a removable optical disk 3326, it will beappreciated by those skilled in the art that other types ofcomputer-readable media which can store data that is accessible by acomputer, such as magnetic cassettes, FLASH memory cards, random accessmemories (RAMs), read only memories (ROM), and the like, can also beused in the exemplary operating environment.

A number of program modules can be stored via the non-volatileread/write memory 3316, magnetic disk 3320, optical disk 3326, ROM 3310,or RAM 3312, including an operating system 3330, one or more applicationprograms 3332, program modules 3334 and program data 3336. Examples ofcomputer operating systems conventionally employed include the NUCLEUS®operating system, the LINUX® operating system, and others, for example,providing capability for supporting application programs 3332 using, forexample, code modules written in the C++® computer programming language.The application programs 3332 and/or the program modules 3334 can alsoinclude a temporal-variation-amplifier (as shown in 3248 in FIG. 32) anda vital sign generator (as shown in 3249 in FIG. 33). In someimplementations, the temporal-variation-amplifier 3248 in theapplication programs 3332 and/or the program modules 3334 includes askin-pixel-identifier 1602, a frequency-filter 1606, regional facialclusterial module 1608 and a frequency filter 1610 as in FIGS. 16 and17. In some implementations, the temporal-variation-amplifier 3248 inapplication programs 3332 and/or the program modules 3334 includes askin-pixel-identifier 1602, a spatial bandpass-filter 1802, regionalfacial clusterial module 1608 and a temporal bandpass filter 1804 as inFIG. 18. In some implementations, the temporal-variation-amplifier 3248in the application programs 3332 and/or the program modules 3334includes a pixel-examiner 1902, a temporal variation determiner 1906 andsignal processor 1908 as in FIG. 19. In some implementations, thetemporal-variation-amplifier 3248 in the application programs 3332and/or the program modules 3334 includes a skin-pixel-identificationmodule 2002, a frequency-filter module 2008, spatial-cluster module 2012and a frequency filter module 2016 as in FIGS. 20 and 21. In someimplementations, the temporal-variation-amplifier 3248 in theapplication programs 3332 and/or the program modules 3334 includes askin-pixel-identification module 2002, a spatial bandpass filter module2302, a spatial-cluster module 2012 and a temporal bandpass filtermodule 2306 as in FIG. 23. In some implementations, thetemporal-variation-amplifier 3248 in the application programs 3332and/or the program modules 3334 includes a pixel-examination-module2402, a temporal variation determiner module 2406 and a signalprocessing module 2410 as in FIG. 24. The solid-state image transducer328 captures images 330 that are processed by thetemporal-variation-amplifier 3248 and the vital sign generator 3249 togenerate the vital sign(s) 1616 that is displayed by display 3350 ortransmitted by computation resource 3302, enunciated by a speaker orstored in program data 3336.

A user can enter commands and information into computation resource 3302through input devices such as input media 3338 (e.g., keyboard/keypad,tactile input or pointing device, mouse, foot-operated switchingapparatus, joystick, touchscreen or touchpad, microphone, antenna etc.).Such input devices 3338 are coupled to the processing unit 3304 througha conventional input/output interface 3342 that is, in turn, coupled tothe system bus. Display 3350 or other type of display device is alsocoupled to the system bus 3308 via an interface, such as a video adapter3352.

The computation resource 3302 can include capability for operating in anetworked environment using logical connections to one or more remotecomputers, such as a remote computer 3360. The remote computer 3360 canbe a personal computer, a server, a router, a network PC, a peer deviceor other common network node, and typically includes many or all of theelements described above relative to the computation resource 3302. In anetworked environment, program modules depicted relative to thecomputation resource 3302, or portions thereof, can be stored in aremote memory storage device such as can be associated with the remotecomputer 3360. By way of example, remote application programs 3362reside on a memory device of the remote computer 3360. The logicalconnections represented in FIG. 33 can include interface capabilities,e.g., such as interface capabilities in FIG. 14, a storage area network(SAN, not illustrated in FIG. 33), local area network (LAN) 3372 and/ora wide area network (WAN) 3374, but can also include other networks.

Such networking environments are commonplace in modern computer systems,and in association with intranets and the Internet. In certainimplementations, the computation resource 3302 executes an Internet Webbrowser program (which can optionally be integrated into the operatingsystem 3330), such as the “Internet Explorer®” Web browser manufacturedand distributed by the Microsoft Corporation of Redmond, Wash.

When used in a LAN-coupled environment, the computation resource 3302communicates with or through the local area network 3372 via a networkinterface or adapter 3376 and typically includes interfaces, such as amodem 3378, or other apparatus, for establishing communications with orthrough the WAN 3374, such as the Internet. The modem 3378, which can beinternal or external, is coupled to the system bus 3308 via a serialport interface.

In a networked environment, program modules depicted relative to thecomputation resource 3302, or portions thereof, can be stored in remotememory apparatus. It will be appreciated that the network connectionsshown are exemplary, and other means of establishing a communicationslink between various computer systems and elements can be used.

A user of a computer can operate in a networked environment usinglogical connections to one or more remote computers, such as a remotecomputer 3360, which can be a personal computer, a server, a router, anetwork PC, a peer device or other common network node. Typically, aremote computer 3360 includes many or all of the elements describedabove relative to the computer 3300 of FIG. 33.

The computation resource 3302 typically includes at least some form ofcomputer-readable media. Computer-readable media can be any availablemedia that can be accessed by the computation resource 3302. By way ofexample, and not limitation, computer-readable media can comprisecomputer storage media and communication media.

Computer storage media include volatile and nonvolatile, removable andnon-removable media, implemented in any method or technology for storageof information, such as computer-readable instructions, data structures,program modules or other data. The term “computer storage media”includes, but is not limited to, RAM, ROM, EEPROM, FLASH memory or othermemory technology, CD, DVD, or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other media which can be used to storecomputer-intelligible information and which can be accessed by thecomputation resource 3302.

Communication media typically embodies computer-readable instructions,data structures, program modules or other data, represented via, anddeterminable from, a modulated data signal, such as a carrier wave orother transport mechanism, and includes any information delivery media.The term “modulated data signal” means a signal that has one or more ofits characteristics set or changed in such a manner as to encodeinformation in the signal in a fashion amenable to computerinterpretation.

By way of example, and not limitation, communication media include wiredmedia, such as wired network or direct-wired connections, and wirelessmedia, such as acoustic, RF, infrared and other wireless media. Thescope of the term computer-readable media includes combinations of anyof the above.

FIG. 34 is a representation of display 3400 that is presented on thedisplay device of apparatus in FIGS. 3-14 and 35-39, according to animplementation.

Some implementations of display 3400 include a representation of threedetection modes 3402, a first detection mode being detection and displayof surface temperature, a second detection mode being detection anddisplay of body temperature and a third detection mode being detectionand display of room temperature.

Some implementations of display 3400 include a representation of Celsius3404 that is activated when the apparatus is in Celsius mode.

Some implementations of display 3400 include a representation of asensed temperature 3406.

Some implementations of display 3400 include a representation ofFahrenheit 3408 that is activated when the apparatus is in Fahrenheitmode.

Some implementations of display 3400 include a representation of a mode3410 of site temperature sensing, a first site mode being detection ofan axillary surface temperature, a second site mode being detection ofan oral temperature, a third site mode being detection of a rectaltemperature and a fourth site mode being detection of a coretemperature.

Some implementations of display 3400 include a representation of atemperature traffic light 3412, in which a green traffic light indicatesthat the temperature 320 is good; an amber traffic light indicates thatthe temperature 320 is low; and a red traffic light indicates that thetemperature 320 is high.

Some implementations of display 3400 include a representation of a probemode 3414 that is activated when the sensed temperature 3406 is from acontact sensor.

Some implementations of display 3400 include a representation of thecurrent time/date 3416 of the apparatus.

FIG. 35-39 are schematics of the electronic components of a non-touchthermometer 3500 having a digital IR sensor. FIG. 35 is a portion of theschematic of the non-touch thermometer 3500 having a digital IR sensor,according to an implementation. As discussed above in regards to FIG. 4and FIG. 3, thermal isolation of the digital IR sensor is an importantfeature. In a second circuit board 3501, a digital IR sensor 308 isthermally isolated from the heat of the microprocessor 3504 (shown inFIG. 36) through a first digital interface 3502. The digital IR sensor308 is not mounted on the same circuit board 3505 as the microprocessor3504 (shown in FIG. 36) which reduces heat transfer from a first circuitboard 3505 to the digital IR sensor 308. The non-touch thermometer 3500also includes a second circuit board 3501, the second circuit board 3501including a second digital interface 3512, the second digital interface3512 being operably coupled to the first digital interface 3502 and adigital infrared sensor 308 being operably coupled to the second digitalinterface 3512, the digital infrared sensor 308 having ports thatprovide only digital readout. The microprocessor 3504 (shown in FIG. 36)is operable to receive from the ports that provide only digital readouta digital signal that is representative of an infrared signal generatedby the digital infrared sensor 308 and the microprocessor 3504 (shown inFIG. 36) is operable to determine a temperature from the digital signalthat is representative of the infrared signal. The first circuit board3505 includes all of the components in FIG. 35, FIG. 36 and FIG. 37other than the second circuit board 3501, the digital IR sensor 308 andthe second digital interface 3512.

FIG. 36 is a portion of the schematic of the non-touch thermometer 3500having the digital IR sensor, according to an implementation. Anon-touch thermometer 3500 includes a first circuit board 3505, thefirst circuit board 3505 including the microprocessor 3504.

FIG. 37 is a portion of the schematic of the non-touch thermometer 3500having the digital IR sensor, according to an implementation. The firstcircuit board 3505 includes a display device that is operably coupled tothe microprocessor 3504 through a display interface 3508.

FIG. 38 is a portion of the schematic of the non-touch thermometer 3500having the digital IR sensor, according to an implementation. Circuit3500 includes a battery 3506 that is operably coupled to themicroprocessor 3504, a single button 3510 that is operably coupled tothe microprocessor 3504.

FIG. 37 is a portion of the schematic of the non-touch thermometer 3500having the digital IR sensor, according to an implementation.

The non-touch thermometer further includes a housing, and where thebattery 304 is fixedly attached to the housing. The non-touchthermometer where an exterior portion of the housing further includes amagnet.

In some implementations, the microprocessor 302, microprocessor 604,microprocessor 3504 in FIG. 35, main processor 3202 in FIG. 32 orprocessing unit 3304 in FIG. 33 that do not use the digital infraredsensor 308 can be a digital signal processor (DSP) that is specializedfor signal processing such as the Texas Instruments® C6000 series DSPs,the Freescale® MSC81xx family.

In some implementations, the microprocessor 604, microprocessor 3504 inFIG. 35, main processor 3202 in FIG. 32 or processing unit 3304 in FIG.33 can be a graphics processing unit GPU that use a specializedelectronic circuit designed to rapidly manipulate and alter memory toaccelerate the creation of images in a frame buffer, such as the Nvidia®GeForce 8 series.

In some implementations, the microprocessor 302, microprocessor 604,microprocessor 3504 in FIG. 35, main processor 3202 in FIG. 32 orprocessing unit 3304 in FIG. 33 can be field-programmable gate array(FPGA) that is an integrated circuit designed to be configured by acustomer or a designer after manufacturing according to a hardwaredescription language (HDL) using programmable logic components called“logic blocks”, and a hierarchy of reconfigurable interconnects thatallow the blocks to be “wired together” that are changeable logic gatesthat can be inter-wired in different configurations that perform analogfunctions and/or digital functions. Logic blocks can be configured toperform complex combinational functions, or merely simple logic gatessuch as AND and XOR. In most FPGAs, the logic blocks also include memoryelements, which may be simple flip-flops or more complete blocks ofmemory.

FIG. 40 is a block diagram of a solid-state image transducer 4000,according to an implementation. The solid-state image transducer 4000includes a great number of photoelectric elements, a.sub.1 . . . sub.1,a.sub.2 . . . sub.1, . . . , a.sub.mn, in the minute segment form,transfer gates TG1, TG2, . . . , TGn responsive to a control pulseV.sub.φP for transferring the charges stored on the individualphotoelectric elements as an image signal to vertical shift registersVS1, VS2, . . . , VSn, and a horizontal shift register HS fortransferring the image signal from the vertical shift registers VSs,through a buffer amplifier 2 d to an outlet 2 e. After the one-frameimage signal is stored, the image signal is transferred to verticalshift register by the pulse V.sub.φP and the contents of the verticalshift registers VSs are transferred upward line by line in response to aseries of control pulses V.sub.φV1, V.sub.φV2. During the time intervalbetween the successive two vertical transfer control pulses, thehorizontal shift register HS responsive to a series of control pulsesV.sub.φH1, V.sub.φH2 transfers the contents of the horizontal shiftregisters HSs in each line row by row to the right as viewed in FIG. 40.As a result, the one-frame image signal is formed by reading out theoutputs of the individual photoelectric elements in such order.

FIG. 41 is a block diagram of the communication subsystem 338, accordingto an implementation. The communication subsystem 338 includes areceiver 4100, a transmitter 4102, as well as associated components suchas one or more embedded or internal antenna elements 4104 and 4106,Local Oscillators (LOs) 4108, and a processing module such as a DigitalSignal Processor (DSP) 4110. The particular implementation of thecommunication subsystem 338 is dependent upon communication protocols ofa wireless network 4105 with which the mobile device is intended tooperate. Thus, it should be understood that the implementationillustrated in FIG. 41 serves only as one example. Examples of thehand-held medical-data capture-device 104 include mobile device 3200,non-touch biologic detector in FIG. 3-3, apparatus that estimates a bodycore temperature 4-10, apparatus of variation amplification FIGS. 36-20and 22-24 and non-touch thermometer 3500. Examples of the wirelessnetwork 4105 include network 3205 in FIG. 32

Signals received by the antenna 4104 through the wireless network 4105are input to the receiver 4100, which may perform such common receiverfunctions as signal amplification, frequency down conversion, filtering,channel selection, and analog-to-digital (A/D) conversion. A/Dconversion of a received signal allows more complex communicationfunctions such as demodulation and decoding to be performed in the DSP4110. In a similar manner, signals to be transmitted are processed,including modulation and encoding, by the DSP 4110. These DSP-processedsignals are input to the transmitter 4102 for digital-to-analog (D/A)conversion, frequency up conversion, filtering, amplification andtransmission over the wireless network 4105 via the antenna 4106. TheDSP 4110 not only processes communication signals, but also provides forreceiver and transmitter control. For example, the gains applied tocommunication signals in the receiver 4100 and the transmitter 4102 maybe adaptively controlled through automatic gain control algorithmsimplemented in the DSP 4110.

The wireless link between the hand-held medical-data capture-device 104and the wireless network 4105 can contain one or more differentchannels, typically different RF channels, and associated protocols usedbetween the hand-held medical-data capture-device 104 and the wirelessnetwork 4105. An RF channel is a limited resource that must beconserved, typically due to limits in overall bandwidth and limitedbattery power of the hand-held medical-data capture-device 104.

When the hand-held medical-data capture-device 104 is fully operational,the transmitter 4102 is typically keyed or turned on only when it istransmitting to the wireless network 4105 and is otherwise turned off toconserve resources. Similarly, the receiver 4100 is periodically turnedoff to conserve power until the receiver 4100 is needed to receivesignals or information (if at all) during designated time periods.

The PMR 103 is received by the communication subsystem 338 from the mainprocessor 3202 at the DSP 4110 and then transmitted to the wirelessnetwork 4105 through the antenna 4104 of the receiver 4100.

A non-touch biologic detector or thermometer that senses temperaturethrough a digital infrared sensor, and transmits the temperature to anelectronic medical record system. A technical effect of the apparatusand methods disclosed herein electronic transmission of a body coretemperature that is estimated from signals from the non-touchelectromagnetic sensor to a heterogeneous electronic medical recordsystem. Another technical effect of the apparatus and methods disclosedherein is generating a temporal variation of images from which a vitalsign can be transmitted to a heterogeneous electronic medical recordsystem. Although specific implementations are illustrated and describedherein, it will be appreciated by those of ordinary skill in the artthat any arrangement which is generated to achieve the same purpose maybe substituted for the specific implementations shown. This applicationis intended to cover any adaptations or variations.

In particular, one of skill in the art will readily appreciate that thenames of the methods and apparatus are not intended to limitimplementations. Furthermore, additional methods and apparatus can beadded to the modules, functions can be rearranged among the modules, andnew modules to correspond to future enhancements and physical devicesused in implementations can be introduced without departing from thescope of implementations. One of skill in the art will readily recognizethat implementations are applicable to future non-touch temperaturesensing devices, different temperature measuring sites on humans oranimals and new display devices.

The terminology used in this application meant to include alltemperature sensors, processors and operator environments and alternatetechnologies which provide the same functionality as described herein.

The invention claimed is:
 1. A non-touch thermometer to measure a human vital sign, the non-touch thermometer comprising: a microprocessor; a battery operably coupled to the microprocessor; a single button operably coupled to the microprocessor; a camera operably coupled to the microprocessor and operable to capture at least two images to a memory; wherein the microprocessor includes a pixel-examination-module that is operable to examine pixel values of the at least two images in the memory, a temporal-variation module that is operable to determine temporal variation of the pixel values between the at least two images, a signal processing module that is operable to amplify the temporal variation resulting in amplified temporal variation, and a vital-sign generator that is operably coupled to the signal processing module that generates the human vital sign from the temporal variation; a wireless communication subsystem that is operably coupled to the microprocessor and that is operable to transmit a representation of the human vital sign; and a display device that is operably coupled to the microprocessor that displays the human vital sign, wherein the wireless communication subsystem further comprises a component that is operable to transmit a representation of date and time, operator identification, patient identification and manufacturer, model number and firmware revision of the non-touch thermometer.
 2. The non-touch thermometer of claim 1, wherein the signal processing module is further configured to amplify variations of the pixel values between the at least two images.
 3. The non-touch thermometer of claim 1, wherein the signal processing module performs temporal processing.
 4. The non-touch thermometer of claim 3, wherein the temporal processing is a bandpass filter.
 5. The non-touch thermometer of claim 4, wherein the bandpass filter is configured to analyze frequencies over time.
 6. The non-touch thermometer of claim 1, wherein the signal processing module performs spatial processing.
 7. The non-touch thermometer of claim 1 wherein the wireless communication subsystem transmits to a static Internet Protocol address in order to reduce Internet Protocol discovery burden on the device.
 8. The non-touch thermometer of claim 1 wherein the non-touch thermometer does not support specific discovery protocols or domain name service.
 9. The non-touch thermometer of claim 1 wherein a connection is established and data is pushed from the non-touch thermometer through the wireless communication subsystem, thereafter an external device controls flow of the data between the non-touch thermometer and the external device, wherein the connection further comprises: an authenticated communication channel.
 10. The non-touch thermometer of claim 1, the wireless communication subsystem is configured to operate on a specific segment of a network.
 11. The non-touch thermometer of claim 1, wherein the wireless communication subsystem transmits through an Internet Protocol tunnel.
 12. The non-touch thermometer of claim 1, the microprocessor further comprising: a camera operably coupled to the microprocessor and providing at least two images to the microprocessor; and a pixel-examination-module configured to examine pixel values of the at least two images, a temporal-variation module to determine temporal variation of the pixel values between the at least two images being below a particular threshold, a signal processing module configured to amplify the temporal variation resulting in amplified temporal variation, and a visualizer to visualize a pattern of flow of blood in the amplified temporal variation in the at least two images.
 13. The non-touch thermometer of claim 1 further comprising: a digital infrared sensor operably coupled to the microprocessor, the digital infrared sensor having only digital readout ports, the digital infrared sensor having no analog sensor readout ports; and wherein the microprocessor is operable to receive from the digital readout ports a digital signal that is representative of an infrared signal detected by the digital infrared sensor and the microprocessor is operable to determine a temperature from the digital signal that is representative of the infrared signal.
 14. The non-touch thermometer of claim 13 wherein no analog-to-digital converter is operably coupled between the digital infrared sensor and the microprocessor.
 15. The non-touch thermometer of claim 13 wherein the temperature further comprises a body core temperature and wherein determining the body core temperature is based on a cubic relationship representing three thermal ranges between a numerical representation of electromagnetic energy of an external source point and the body core temperature, wherein the cubic relationship includes a coefficient representative of different relationships between the external source point and the body core temperature in the three thermal ranges.
 16. The non-touch thermometer of claim 1, the microprocessor further comprising: a cropper that is operable to receive at least two images and that is operable to crop each of the images to exclude a border area of the images, generating at least two cropped images. 